Urban Futures for Central Canada: Perspectives on Forecasting Urban Growth and Form 9781442632332

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Urban futures for Central Canada

Studies in this volume directed by Centre for Urban and Community Studies University of Toronto RELATED PUBLICATIONS

Urban systems development in Central Canada: Selected papers Edited by L.S. Bourne and R.D. MacKinnon The form of cities in Central Canada: Selected papers Edited by L.S. Bourne, R.D. MacKinnon, and J.W. Simmons

Urban futures for Central Canada: Perspectives on forecasting urban growth and form EDITED BY

Larry S. Bourne Ross D. MacKinnon Jay Siegel James W. Simmons

UNIVERSITY OF TORONTO PRESS

©University of Toronto Press 1974 Toronto and Buffalo Printed in Canada ISBN 0-8020-2144-1 (cloth) 0-8020-6243-1 (paper) LC 73-92297

Contents

ACKNOWLEDGMENTS INTRODUCTION I

3

FORECASTS OF URBAN GROWTH Editors' Comments 1 Defining the future urban system James W. Simmons and Larry S. Bourne 2 Forecasting township populations of Ontario, from time-space covariances Leslie Curry and Geoffrey Bannister 3 Forecasting urban populations Jay Siegel 4 Long-range employment forecasting for the Toronto metropolitan region John R. Miron

II

vii

23 25

34 60

79

GROWTH AND THE URBAN SYSTEM Editors' Comments 5 Urban growth and the urban hierarchy Jay Siegel and Monty Woodyard 6 The components of interurban migration streams Monty Woodyard

95 98

116

7

8 9 10

11

III

Future interurban transportation in Central Canada Ross D. MacKinnon Intercity linkage patterns James W. Simmons and Ian J. Lindsay Forecasting the regional economy of Ontario John N.H. Britton and Gerald M. Barber Spatial-temporal relationships in the Quebec urban system Claude Marchand The effects of public policy on the future urban system Hans Blumenfeld

132 140 158

178

194

GROWTH AND URBAN FORM Editors' Comments 12 Trends in future urban land use Larry S. Bourne and Peter D. Harper 13 Urban transportation in the future Ross D. MacKinnon 14 Household movement trends and social change James W. Simmons 15 The city in the periphery Gerald Hodge 16 The form and function of future communities Barry Wellman

209 213 236 265 281 301

APPENDIXES A B

Population forecasts for townships in Ontario, 1971-2001 Population forecasts for cities in Central Canada, 1971-2001

315 329

Acknowledgments

Many people have contributed to the preparation of this volume and to completion of the research projects from which it derives. These people are already aware of our appreciation. The principal research project behind the papers in this volume is the Urban Environment Study. This study was directed by the Centre for Urban and Community Studies at the University of Toronto and was supported by a long-term grant from Bell Canada (Montreal). We gratefully acknowledge this generous support for academic research. For those papers deriving from other sources appropriate acknowledgment is made in the text. In the final analysis the successful completion of these research efforts depends on effective communication of the results. The cartographic displays contribute towards this goal; they were prepared by Jennifer Wilcox and Jane Ejima in the cartographic office of the Department of Geography. We gratefully acknowledge the contribution of Sheila Talley, Elaine Orr, and Bev Thompson in the Centre for Urban and Community Studies who were able to translate our unintelligible handwriting into neatly typed drafts. Professor J. Stefan Dupré provided the initial stimulus for the study and was a stimulating force throughout its execution. Finally, R.I.K. Davidson and Joan Bulger at University of Toronto Press were most helpful in seeing the manuscript through the editorial process and in suggesting ways to improve the style

viii

Acknowledgments

of presentation; and Gwendolyn Peroni expertly prepared the final typed copy for publication. Larry S. Bourne Ross D. MacKinnon Jay Siegel James W. Simmons Toronto

September 1973

Urban futures for Central Canada

Introduction

From the train of moving seats in the darkest building, a visitor looks down on a miniature landscape far away ... and finally he beholds the city itself with its quartermile high towers, huge glass, and soaring amongst them four-level, seven-lane directional highways on which you can surely choose your speed — 100, 200 miles an hour. The city ... has abundant functions: fresh air, fine green parkways, recreational centers, all results of plausible planning and design. No building's shadow will touch another. Parks will occupy one-third of the city. ('View of the City in 1960, from the World's Fair, 1939,' in Daedalus, 1967). Images of the future city abound. Some, such as the one quoted above, are based on intelligent subjective speculations but have little or no basis in fact. In this case the forecast may not be wrong but the time horizon is. Others are more cautious and less speculative, based on reasoned evaluations and projections of past trends and relationships. Neither approach is necessarily better; both can be useful. And both can be wrong. The research reported in the following pages tends towards the latter of these two courses. It is argued that one cannot understand the city of the future if one does not understand the city of the present and the recent past. Urban issues have suddenly emerged in the last few years as a dominant element in Canadian political life. This change represents a major if not drastic revision in society's

4

Urban futures for Central Canada

view of its problems and priorities. It is a change expressed in numerous ways: in the tenor of political speeches, in the content of our morning newspapers, in seminars and debates on public affairs, and in the flow of research materials from public agencies, institutions, and individuals. Many observers are now asking and debating the same questions: what is the state of the country as an emerging urban nation, what are the dominant trends in urban development, and what are the consequences of these trends for economic and social well-being in cities? In short, what is the urban future to be like and what can be done about it? OBJECTIVES This volume is concerned with urban futures. It contains a series of essays on the future form and character of the heartland of urban Canada. This heartland, essentially the St Lawrence-Great Lakes lowlands of southern Ontario and Quebec, we have chosen to title urban Central Canada.1 At the time of the last census this area contained nearly 14 million people, or over 63 per cent of the Canadian total, and a far higher percentage of the nation's industrial production, economic wealth, and decision-making power. It had, in 1971, 12 of the country's 22 metropolitan areas and 66 per cent of the total urban population, and was itself over 81 per cent urbanized. Estimates of future growth for Canada, and Ontario and Quebec (table I.I), suggest that this dominant position will be maintained, if not increased. The following essays, 16 in all, treat aspects of urbanization in this rapidly changing and evolving environment. Three themes establish the background for each of the essays. One is essentially that of forecasting: providing a spectrum of research methods and approaches which can be used to anticipate the future spatial distribution of population and economic activity in urban Central Canada. The second is the identification of consequences of trends in urban development and of the projections of these trends; while the third is an assessment of the role of public policy. These themes are expressed in a wide variety of research topics: the structure and growth of the system of cities, migration and mobility, transportation and interaction, land use and economic structure, communities and neighbourhoods. The essays are primarily research reports rather than reviews or state-of-the-art assessments of urban research

Introduction TABLE I.I Aggregate population estimates:

CENTRAL

Prairies

5

Canada, regional/ and urban, 2001 Region 1 West Atlantic Coast

North

Canada TOTALS

1971 ACTUAL POPULATION Numbers ( in millions) % of national total % urban

13.7

63 . 6 81.7

3.5

2.2

2.1

16.5 68.4

10.1 75.7

54.7

0.3 60.1

100.0 76.1

9.5

.05

21.6

2001 ESTIMATED POPULATION2 Numbers (in millions) % of national total., 3 % urban

20.4

4.3

4.0

2.3

0.1

31.1

65.9 88.1

14.0 78.2

12.8 84.5

7.1 72.3

0.3 71.7

100.0 86.2

ESTIMATED INCREASE 1971-2001 Numbers (in millions) % change % of total change 1 2 3

6.7 49.0

0.8 22.9

1.8 81.8

0.2 9.5

0.05 100.0

9.5 44.0

70.2

8.4

18.8

2.1

0.5

100.0

Provincial totals (some differences in totals appear due to rounding error) Median projections only from various sources Population living in incorporated urban areas with populations over 1,000

in Canada. They vary in their treatment of the future from the heavily methodological and statistical to the largely speculative and subjective. However few tend to be normative in approach or inclination. Instead they seek to demonstrate some of the results of an extensive academic research program in forecasting Canada's urban future. Forecasting, in whatever form, is a precarious occupation,

6

Urban futures for Central Canada

both for the researcher and for the consumer. Part of the problem is the ineluctable fact that man cannot predict the historical future. The only thing we know for certain is that the future will be different from the past. Moreover one cannot escape value predicaments, particularly in the context of today's unstable societies - what Vickers (1972) calls 'freedom in a rocking boat1 - nor escape the dangers of the forecasts becoming the end product rather than a means to an end (see Cole, et al., 1973, reviewing Forrester and Meadows, World Dynamics). These dangers are most pronounced in those studies in which a single, and usually computer-based, forecasting approach is employed (Forrester, 1969). The authors in this volume are aware of these issues and difficulties. There are, of course, different types of forecasting and prediction (see paper 3), as there are different types of futures. The organization of this volume, the multiplicity of authors, and the range of perspectives on the future form of urbanization are a response to these issues and to the question of growth itself (Meadows, 1972). The specific research results reported here derive in the main but not exclusively from one major research project, the Urban Environment Study, undertaken at the University of Toronto from 1968 through 1972.2 This volume builds on the publication of two earlier volumes emanating from the same project, one summarizing research on the development of the urban system in Central Canada (Bourne and MacKinnon, 1972), and the other treating examples of the changing internal form and structure of cities in the same region (Bourne, MacKinnon, and Simmons, 1973). The interested reader is referred to both of these books for background information. The Urban Environment Study which spawned these publications had one notable characteristic which is directly reflected in the emphases and organization of the essays in this volume. It consisted of a series of individual component studies, the number and content of which changed as conditions warranted, set within a broad frame of reference. This flexibility permitted an unusually wide range of specific research objectives and approaches to be accommodated within the study guidelines. In addition, as the study and preparation of this volume evolved over time, other participants and results from parallel projects were brought in under a more general research umbrella to strengthen and expand the range of topics covered.

Introduction

7

THE URBAN SYSTEM The principal focus of this volume is the urban system of Central Canada. The term system is used here in its most general sense. It implies a set of objects (cities), and an external environment (the nation, the national and international economy), in which the objects (cities) are more closely linked with each other than with objects outside the system, and in which the member objects interact together with that environment (Jantsch, 1972). Pred (1973) and Berry (1973) have recently provided extensive and stimulating reviews of these ideas as applied to the growth and operation of urban systems in a historical as well as a spatial context. Specifically one can identify a hierarchy of different systems of interest here (see part I). These can be summarized as: (1) the international urban system, notably for Canada that of the United States to which it is linked by trade and capital flows and migration; (2) the Canadian national urban system of which our study area is an integral part; (3) the regional urban system of Central Canada and its various subsystems, particularly those subsystems centred on Toronto and Montreal; and (4) the individual metropolitan area, that is, the 'daily1 urban system defined largely by the extent of commuting to work and daily travel patterns. The daily urban system is, in turn, comprised of a large number of interacting subsystems (land, housing, transportation, social groups) which combine to make up the complex contemporary metropolis. And urban systems at all levels represent one type of 'complex social system1 with all the attributes that that implies (Emery and Trist, 1972). The number and size of cities which presently comprise the regional urban system of Central Canada are displayed in table 1.2. The cities in this table are the largest urban centres in Ontario and Quebec - those defined in 1 functional' terms based on the census designations of metropolitan area and major urban agglomeration. They are in fact the closest approximations we have to the concept of the daily urban system. Unfortunately these are not the exact areas and populations on which the bulk of research reported in the following pages is based. The detailed 1971 Census returns were not available at the time of writing. In addition, the urban agglomeration category was new in 1971, and few statistics are published for this category or

TABLE 1.2 Population of urban centres in Central Canada, 1941-71

No. Urban area

METROPOLITAN AREAS 1 Montreal 2 Toronto 3 Ottawa-Hull 4 Hamilton 5 Quebec City 6 Niagara-St Catharines 7 London 8 Windsor 9 Kitchener 10 Sudbury 11 Chicoutimi-Jonquiere 12 Thunder Bay

Population (in OOOs) 1941 1956 1951 1961

1,145 910 226 198 225 78 91 124 70 56 43 42

1966

1,472 1,210

1,745 1,502

2,110 1,825

293 280 276 131 129 164 107 74 76 68

345 338 312 164 154 186 129 98 91 80

430 395 358 217 181 193 155 111 105 92

63 75 56 62 46 52 51 44 35

81 88 63 70 65 56 61 52 44

100 94 72 80 75 62 67 56 51

59 21

66 24

65 42

18

44

46

MAJOR URBAN AGGLOMERATIONS (over 30,000) 13 Oshawa-Whitby 33 50 14 Trois Rivieres 42 66 15 Kingston 48 30 16 Sherbrooke 38 55 17 Sault Ste Marie 26 38 18 Brantford-Paris 32 47 19 Sarnia 40 30 20 Peterborough 25 40 21 Guelph 29 23 50 22 Shawinigan 31 23 North Bay 18 16 24 Cornwall3 14 17

1966"1"

2,437 2,571 2,159 2,290 495 529 457 449 437 413 229 286 207 254 212 238 192 192 117 137 109 133 98 108

1971

I

2,743 2,628 603 499 480 303 286 259 227 155 134 112

106 95 82 80 76 75 74 61 54 62

120 98 86 85 81 80 78 64 63

-

47

57 49

Table 1.2 continued

No. Urban area

25 Drummondville3 26 27 28 29 30 31 32 33

St Jean Timmins St Hyacinthe Granby Barrie Valleyfield St Jerome Sorel

1941 11 17 29 18 14 10 17 11 13

1951 35 25 37 20 22 13 24 18 19

1956 37 31 37 20 27 17 26 21 23

OTHER MAJOR AGGLOMERATIONS AND CITIES OVER 10,000 22 21 17 34 Chatham 21 20 16 35 Belleville 12 10 8 36 Trenton 17 16 13 37 Joliette 15 7 12 38 Rimouski 27 24 13 39 Rouyn-Noranda 16 13 9 40 Victoriaville 20 15 13 41 Thetford Mines 18 16 13 42 Woodstock 6 43 Baie Comeau 11 8 44 Alma 14 11 12 45 Brockville 9 46 Cobourg 47 Cowansville 48 Gaspe4 49 Kapuskasing 10 9 50 Kenora 51 Lachute

1961

1966 19661

19711

39 39 40 22 31 21 32 29 25

43 43 40 24 34 24 34 33 30

46 44 42 38 40 32 37 33 34

47 47 41 40 39 38 37 35 35

30 31 13 18 18 30 19 22 21 14 13 18 11 7 7 11 8

32 33 14 19 20 30 21 22 24 24 22 19 12 11 13 11 10

27 27 27 30 25 26 24 -

35 35 29 29 29 29 27 26 26 25 22 20 11 12 17 13 11 12

Table 1.2 continued No. Urban area 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69

1

La Tuque Leamington Lincoln^ Lindsay Magog Matane Midland Montmagny Orillia Owen Sound Pembroke Riviere-du-Loup Ste Scholastique Sept lies Simcoe Stratford Val d'Or Wallaceburg

1941

1951

1956

1961

1966

10 _

11

—

13 _

14 10

9 10 14 11 —

10 12 14 16 13 9

10 13 18 17 15 10

11 13 9 9 7 20 17 17 11

12 14 11 10 12 21 18 16 12

17 -

19 -

6 20 10 -

14 21 11 8

19 10 23 12 11

19661

-

19711 13 10 14 13 13 12 11 12 24 19 17 13 15 24 11 25 17 11

Expanded 1971 Census definitions; figures not directly comparable to previous figures 2 St Catharines, Niagara Falls, Welland and adjoining territory in the Niagara peninsula were merged in the 1971 Census to form the Niagara-St Catharines metropolitan area 3 Municipality only; population growth due largely to annexation 4 New town formed by municipal reorganization

Introduction

11

for its predecessor, the major urban area. In 1966, the final census date for most of our analyses (at least in those studies which used census data), there were 69 urban centres in Central Canada with populations over 10,000 (see Bourne and MacKinnon, 1972). The important point here is that the urban system, as a definitional entity and a concrete reality, is constantly evolving. With each census some centres are aggregated in order to bring definitions in line with economic, social, and geographic realities. But what one gains in realism by aggregating to increasingly larger units, one loses in terms of information and in historical continuity. Several centres have disappeared (statistically, that is) since previous studies: for example, Niagara Falls, Welland, and Port Colborne were amalgamated in 1971 with St Catharines to form the Niagara metropolitan area; Brampton was enveloped by Toronto; St Thomas by London; and so forth. Other centres have been created by the service needs of major public and private investments, as at Ste Scholastique for the new Montreal international airport. The population figures given in table I.2 reveal a number of general trends which are worth summarizing briefly here. First, through repeated census aggregation the number of major urban centres in Central Canada has not increased: and urban growth continues to be concentrated in a system of metropolitan regions. By the Census of 2001 most if not all of the urban agglomerations in table I.I with populations over 50,000 are likely to be classed as metropolitan centres. Even some of these may themselves disappear through merging: Oshawa-Whitby into Toronto, Guelph into Kitchener-Waterloo, and Brantford into Hamilton or Kitchener or both; and all three may merge with Toronto into a 'consolidated' urban region along the lines the US Census already uses. Or the metropolitan area definition may itself vanish before the turn of the century in recognition of the continual blurring of traditional differences between urban and rural life styles. Second, the reader who quickly calculates recent growth rates will find sharp differences between cities of different sizes and between regions. Metropolitan areas tend to show the largest and most stable rates of increase. Population concentration is continuing apace. Aside from metropolitan centres, the most rapidly growing agglomerations include Barrie, Guelph, Oshawa-Whitby, and Sorel, all on the boun-

12

Urban futures for Central Canada

dary of the metropolitan urban 'field,1 or daily urban systems of Toronto and Montreal. Note that other rapidly growing centres in Ontario, such as Brampton and Georgetown, are included within the expanded 1971 metropolitan area boundaries of Toronto. Third, the slow growth of smaller peripheral centres in general, but particularly in Quebec, is also apparent. Chicoutimi-Jonquiere, Shawinigan, and Granby, as well as Timmins in Ontario, all recorded absolute declines in population between 1966 and 1971, even though the boundaries of most were expanded by the census. Preliminary statistics for urban agglomerations with populations between 10,000 and 30,000 reveal even more widespread declines, again primarily in Quebec and in the northern and peripheral regions of both provinces. Rouyn-Noranda, Val d'Or, Asbestos, Lachute, and Magog in Quebec, and Kenora in Ontario, all showed absolute declines in population between the 1966 and 1971 Censuses. And their experience is not unique. The implication is clear. Urban decline typical of the intermetropolitan and northern peripheries of both Ontario and Quebec is continuing, if not accelerating. In Quebec the margin of the declining periphery appears to be moving closer to Montreal. By contrast, in Ontario the multiplier effects of Torontofs growth have tended to push the zone of rapid population increase and thus the margin of the periphery, further outward from the metropolitan core. These and other assertions are among the subjects of analysis and debate in this volume. THE CONTEXT A number of studies on the various paths of urban development in different countries and on future patterns of urbanization have been undertaken in response to the growing concern over controlling urban growth and the continued concentration of population. There is much to be learned from this experience which is relevant to the Canadian urban environment. The futuristic work in the United States of 'think-tanks' such as Hudson Institute (Kahn and Weiner, 1968), reports from various government task forces (Advisory Committee on Intergovernmental Relations, 1968; US House of Representatives, 1969; Commission on Population and the American Future, 1972), and professional associations such as the American Institute of Planners (Ewald, 1967), the

Introduction

13

Urban Institute (1969) and the Urban Land Institute (Pickard, 1971) have been most valuable. Relevant insights are also available from Britain, from projects such as that of the Centre for Environmental Studies on future forms of urbanization (Cowan, 1969) and on the future of urban planning itself (Cowan, 1973); and those of the Political and Economic Planning study group on the role of planning in the containment of Megalopolis Britain (Hall, et al. 1973; Clawson and Hall, 1973). Other studies have been carried out independently in Sweden, France, and Denmark, some as part of the Europe 2000 project (European Cultural Foundation, 1971 and 1972) or as working groups within international organizations (EFTA, 1973; OECD, 1973; World Bank, 1972). Of course, if the conceptual net were to be cast even further, the range of futuristic literature becomes overwhelming (World Future Society, 1972; Chinoy, 1972; Emery and Trist, 1972; Abler, et al., 1973; Cole, et al., 1973; McHale, 1973). Numerous attempts have also been made to forecast the form and development of individual cities, far too many to mention here. The better-known studies, not surprisingly, are of the world's great metropolitan centres and urbanized regions: New York (Vernon, 1960); Washington (Lessinger, 1962); London (Hall, 1969); Tokyo (Matsushita, 1968); Detroit (Doxiadis, et al., 1967); and the North-Eastern Seaboard of the United States (Gottman, 1961; Clawson, 1971; Clawson and Hall, 1973), to name but a few. Some have developed models of 'artificial1 cities (Forrester, 1969) to test the implications of alternative policy decisions. Although most such studies tend to reflect individual priorities and problems, they nonetheless raise important issues which will also be addressed in this volume. In Canada the range of available literature on future urbanization is much less but is growing. Considerable stimulus for futures research was provided by the critical reports of the Royal Commission on Canada's Economic Prospects (1957) and the Resources for Tomorrow Conference (1961). More recently the impressive series of reports entitled Urban Canada: Problems and Prospects, spawned by the creation of the new federal Ministry of State for Urban Affairs (Lithwick, 1970; Systems Research Group, 1970), provides substantial background for this volume. In fact several authors in the following papers refer, either for support or in criticism, to this important series. Prior to the establishment of the new ministry the Science Council's

14 Urban futures for Central Canada Committee on Urban Development (1971) commissioned a major report entitled Cities for Tomorrow, outlining recommendations for future urban policies in Canada which draw on applications of scientific research and technology. Also the Privy Council published a study on Environmental Management in Canada (MacNeill, 1971) which contained a lengthy evaluation of future urban environments. Both provide useful and stimulating ideas. Other Canadian writings on the future have been increasing in number, but are less analytical in perspective. Many are tailored to broad social or economic trends (Economic Council, 1969 and 1972; Ontario Economic Council, 1971 and 1972), the new populist mood in urban politics (Powell, 1972; Richardson, 1973), or speculative views on social and technological changes such as those contained in Visions 2020 (Clarkson, 1970) and Target 2067 (Bertin, 1968). On the more local level every city in Canada has, of course, a vision of its own future size and form. Most are of little interest outside that city's particular area of influence, most contain targets rather than projections, and most reveal basically the same assumptions and expectations (Padbury, 1971). Most important are those studies of the future form of major metropolitan regions in Central Canada: for example, studies of Toronto carried out by the Metropolitan Toronto Planning Board (MTPB, 1970); of Montreal by the Institut d'Urbanisme de I1University de Montreal (Quay, 1968; Beauregard, 1972); of south-central Ontario by the Ontario Economic Council (1971); of Ottawa by the National Capital Commission; and of the so-called urban corridor from Quebec City to Windsor (Yeates, 1974) - the Canadian extension of what has been described as the future Great Lakes Megalopolis (Doxiadis et al., 1966) . The value of these studies here is that they provide a comparative context, not so much for their content, as there are so many different, and in some instances divergent, paths of urbanization, as for their different approaches and logical structures. Although the orientation of this volume is somewhat more specific than most of the above, we draw heavily on the methodologies, insights, and research experience of this growing body of literature. CONTENTS Clearly not all aspects of the urban Environment,1 present

Introduction

15

and future, could be treated in one volume. Rather we have selected important areas of concern which represent the best matching between those themes following from the individual research studies cited above and those topics whose inclusion in such a volume would be obvious to anyone. The result is a widely diverse although not entirely comprehensive treatment of the components of urban growth and of future urban forms in Central Canada. Within both the Urban Environment Study and this volume the time horizon of interest in speculating on the 'future' has purposefully been left open. To go beyond the year 2000 seems more like prophecy than social science, while the analysis of changes in the last decade seems primarily of historical interest. Nonetheless the selection of the temporal frame of reference in each essay reflects the psyche of the researcher as well as the nature of his research techniques and data. The definition of 'urban1 was also not specified in the guidelines for the authors in this volume, except that it was suggested that the spatial point of view be emphasized. Again a pluralist approach was undertaken different disciplines and individuals were invited to contribute research results in terms of their own priorities and from their own perspectives. Consequently the papers vary markedly in terms of style and analytical approach. As different components of the study evolved, however, interdependencies developed, and certain components became building blocks for others. As a result, even if the following papers are often not linked to each other explicitly, at least cognizance is taken of each other's findings. Neither have the authors selected a particular model for forecasting. To specify a single type of model to fit all situations would be to imply a degree of understanding of the processes of urbanization and specifically of urbansystems behaviour which does not now exist. Neither do the approaches of the authors conform to any single philosophy or strategy of forecasting.^ While arguments on philosophy are not central to any of the following papers, most would fit under the titles of exploratory, descriptive extrapolation or intuitive speculation (Kahn and Weiner, 1967; Jantsch, 1967 and 1972). The problems of spatial forecasting, however, do receive considerable attention in some papers, an interest which has only recently been apparent in the literature generally (Chisholm, Frey, and Haggett, 1971; Haggett, 1973; Abler, et al., 1973).

16

Urban futures for Central Canada

ORGANIZATION The present volume progresses from the general to the specific. It begins with the broad context of urban population forecasts and then proceeds to disaggregate these forecasts and to assess their implications for constituent parts of the Canadian urban environment. The book is divided into three major parts. Each provides supporting materials for the discussions in following sections in a logical sequence. All three parts are subsequently divided into chapters, each discussing a particular theme emanating from the component studies within the original Urban Environment Study framework. The editors1 overview comments at the beginning of each part provide links among the individual contributions. Tables containing detailed population and economic projections for cities and regions in Ontario and Quebec are available in the appendix.^ The first part 'Forecasts of Urban Growth,1 attempts to set a uniform stage for the following parts. First, the authors discuss the difficulty of defining the urban system under investigation and the problems which arise from differing boundary selections. Clearly the reliability of any exercise in urban analysis and spatial forecasting is very heavily dependent on the specific areal units defined. Other papers in the section take off from this cautionary note: they review alternative forecasting methodologies and compare different urban population forecasts for Ontario and Quebec cities, and report on the specific results of mathematical time-space population and employment forecasting models for townships, urban areas, and the Metropolitan Toronto region. These studies are of interest both for their development of statistical forecasting techniques as well as for the forecasts they provide. The next two parts elaborate on the forecasts and methodologies summarized in part I: first, the origin of specific components of urban growth; and second, the implications of these growth trends and forecasts for future urban forms in Central Canada. The papers in part II document aggregate trends and relationships in the urban system. Discussion concentrates on growth differentials among levels of the urban hierarchy, intercity migration streams and their contribution to urban growth, transportation developments and interaction patterns between cities, changes in the structure of the urban/regional

Introduction

17

economy, the spread of economic growth through the urban system, and finally the anticipated effects on various urban systems of public policy directives from all three levels of government. How can the population forecasts summarized in part I be modified? Can changes in the economic structure, in transportation and communication networks, in migration parameters, or in public policy alter the forecast patterns, and if so in what ways? Phrased differently, how may the wide variations in population projections be explained? In part III attention shifts to the intraurban scale. What are the relationships between the growth of aggregate urban systems and urban form? What impact will the anticipated rates of growth have on the urban landscape? How much can behaviour and attitudes alter the use of existing facilities? These questions are explored in terms of land use and development trends within the city, transportation innovations, the evolution of the urban 'field,1 the future of communities and neighbourhoods, and household-movement trends and their role in social change. Given that not all cities could be covered in such a review, emphasis is placed on specific examples where empirical evidence is available. By the end of this section, although no single vision of the future emerges, the range of possible urban alternatives in Central Canada is fairly clearly defined. A POLITICAL FOOTNOTE What is the likely effect on urban growth in the short run of political events in the last few years in the province of Quebec? What would be the potential impact of increased separation from the rest of Canada in the longer term? Although this is one of the most difficult and important unknowns in Canada's future, the subject is not explored here, because of our general practice of not debating the unknowns or unknowables. Also the arena of future political forms, excepting the areas of urban policy, is outside the context of this research. Nevertheless the preliminary 1971 Census data suggests that political events in the last decade have dampened Quebec's economic growth overall. Whether these events have had any redistributive effect within the urban system of Quebec is difficult, if not impossible, to measure; virtually all centres in Quebec, as elsewhere in Canada, showed a declining rate of population growth, and the absolute decline

18

Urban futures for Central Canada

of several peripheral centres was occurring in any case. Most centres would certainly have continued to show slower population growth with or without the various concomitants of French-Canadian nationalism. Since the relative distribution of urban population and the form of urbanization in the aggregate are the central issues in most of the following papers, the relevance of separatism in whatever form is probably minor. Clearly it might reduce growth overall, particularly in the separated region, and could accelerate certain streams of interprovincial migration. Within Quebec itself the redistributive effect is also likely to be small. Any government in that province will have great difficulty in maintaining a significant level of growth anywhere outside the metropolitan Montreal region. NOTES 1

2

3

4

This title is, of course, not unique (see Ray and Berry, 1965), although the definition of the boundaries is different. The study was administered by the Centre for Urban and Community Studies at the University of Toronto and was supported by a grant from Bell Canada (Montreal). A summary of the project is provided in 'Environment Study: Outline and Overview,1 Centre for Urban and Community Studies, September 1972. There are many different interpretations of forecasting strategies (Daedalus, 1967). They vary in purpose and design from scenario writing, gaming, and historical analogy to probabilistic system models. The most common distinctions, however, are between extrapolation (projections) and forecasting, and between forecasting and prediction. Forecasting is generally taken to be timedependent and phrased in terms of probabilities, while prediction is more a one-shot guess without conditional statements attached. In this volume most authors tend to use the terms forecasting, prediction, and projection synonymously in their most general sense. Other forecasts are available from the authors.

Introduction

19

REFERENCES Abler, R., et al. 1973. Cultural Landscapes of the Future. North Scituate, Mass.: Duxbury Press Advisory Commission on Intergovernmental Relations. 1968. Urban and Rural America: Policies for Future Growth. Washington: US Government Printing Office Axworthy, L., and Gillies, J. 1973. The City: Canada's Problems, Canada's Prospects. Toronto: Butterworth Beauregard, L. 1972. 'Montreal: The Year 2000f in L. Beauregard, ed. Montreal Field Guide. IGU Regional Monograph. Toronto: University of Toronto Press Berry, B.J.L. 1973. The Human Consequences of Urbanization: Divergent Paths of Urbanization in the Twentieth Century. London: Macmi1Ian Bertin, L. 1968. Target 2067: Canada's Second Century. Toronto: Macmillan Bourne, L.S., and MacKinnon, R.D., eds. 1972. Urban Systems Development in Central Canada: Selected Papers. Toronto: University of Toronto Press Bourne, L.S., MacKinnon, R.D., and Simmons, J.W., eds. 1973. The Form of Cities in Central Canada: Selected Papers. Toronto: University of Toronto Press Center for Integrative Studies, School of Advanced Technology. 1969. World Facts and Trends. Binghampton, NY: State University of New York Chinoy, E., ed. 1972. The Urban Future. New York: Lieber and Atherton Chisholm, M., Frey, A., and Raggett, P., eds. 1971. Regional Forecasting. London: Butterworth Clarkson, S. 1970. Visions 2020: Fifty Canadians in Search of a Future. Edmonton: Hurtig Clawson, M. 1971. Suburban Land Conversion in the United States: An Economic and Governmental Process. Baltimore: Johns Hopkins University Press for Resources for the Future, Inc. Clawson, M. and Hall, P. 1973. Planning and Urban Growth: An Anglo-American Comparison. Baltimore: Johns Hopkins University Press for Resources for the Future, Inc. Cole, S-f et al., eds. 1973. Thinking About the Future. Brighton: Sussex University Press Commission on Population and the American Future. 1972. Population and the American Future. Washington: US Government Printing Office

20

Urban futures for Central Canada

Cowan, P., ed. 1970. Developing Patterns of Urbanization: Forecasting the Future of Urban Life. Beverly Hills: Sage Publications Cowan, P., ed. 1973. The Future of Planning. London: Heinemann Daedalus. 1967. Journal of the American Academy of Arts and Sciences. 'Toward the Year 2000' 96: 3 Doxiadis, C.A., et al. 1966. 'Developments Toward Ecumenopolis - The Great Lakes Megalopolis,' Ekistics, 22/128: 14-31 Doxiadis, C.A., et al. 1967. Emergence and Growth of An Urban Region: The Urban Detroit Area. 2: Future Alternatives. Detroit: Detroit Edison Company Economic Council of Canada. 1969. Perspective 1975: Sixth Annual Review. Ottawa: Queen's Printer Economic Council of Canada. 1972. The Years to 1980: Ninth Annual Review. Ottawa: Queen's Printer Emery, F.E., and Trist, E.L. 1972. Towards a Social Ecology. Contextual Appreciations of the Future in the Present. London: P1enum European Cultural Foundation. 1971. Citizen and City in the Year 2000. Kluwer: H. Tulp N.V. European Cultural Foundation. 1972. Europa 2000: Fears and Hopes for European Urbanization. The Hague: Martinus Nijhoff European Free Trade Association. Forthcoming. Towards a National Settlement Strategy. Geneva: EFTA Ewald, W.R., Jr, ed. 1967. Environment for Man: The Next Fifty Years. Bloomington: Indiana University Press Forrester, J.W. 1969. Urban Dynamics. Cambridge, Mass.: MIT Press Frejka, T. 1973. The Future of Population Growth: Alternative Paths to Equilibrium. New York: Wiley Gottmann, J. 1961. Megalopolis. New York: Twenthieth Century Guay, J.P. 1968. 'Montreal: Horizon 2000,' Plan Canada, 9: 95-107 Haggett, P. 1973. 'Forecasting Alternative Spatial, Ecological and Regional Futures: Problems and Possibilities,' in R.J. Chorley, ed., Directions in Geography. London: Methuen. Pp 217-36 Hall, P. 1969 rev. London 2000. London: Faber and Faber. Hall, P., et al. 1973. The Containment of Urban England: 1945-1970. 2 vols. London: Allen and Unwin Harris, B. 1971. 'The City of the Future: The Problem of Optimal Design,1 in L.S. Bourne, ed., Internal Structure of the City. New York: Oxford. Pp. 516-22

Introduction

21

Jantsch, E. 1967. Technological Forecasting in Perspective. Paris: OECD Jantsch, E. 1972. 'Forecasting and the Systems Approach: A Critical Survey,1 Policy Sciences, 3: 475-95 Kahn, H., and Weiner, A.J. 1968. The Year 2000. New York: Macmi1Ian Lessinger, J. 1962. 'The Case for Scatteration: Some Reflections on the National Capital Regional Plan for the Year 2000,' Journal of the American Institute of Planners, 28: 119-34 Lithwick, N.H. 1970. Urban Canada: Problems and Prospects. Ottawa: Central Mortgage and Housing Corporation McHale, J. 1973. 'The Changing Pattern of Futures Research in the U.S.A.,1 Futures, 5: 257-71 MacNeill, J.W. 1971. Environmental Management. Ottawa: Queen's Printer Matsushita, M. 1968. 'Tokyo in 2000 A.D.,' in R. Eels and C. Walton, eds, Man in the City of the Future. New York: Macmi1Ian Meadows, D., et al. 1972. The Limits to Growth. New York: Universe Metropolitan Toronto Planning Board. 1970. 'Urban Form in the Toronto Region, 1995,' Metropolitan Plan Review Report No. 4. Land Use Division, Toronto Ontario Economic Council. 1971. Trends, Issues and Possibilities for Urban Development in Southwestern and Central Ontario. Toronto: OEC Ontario Economic Council. 1972. Ontario: A Society in Transition. Toronto: OEC Organization for Economic Cooperation and Development. 1973. National Urban Growth Policies and Strategies. Evaluation of Implementation Experience and Innovation. Paris: OECD, Environmental Directorate. Mimeo Padbury, P. 1971. The Future: A Bibliography of Issues and Forecasting Techniques. University of Waterloo, Department of Man-Environment Studies Perloff, H.S., ed. 1969. The Quality of the Urban Environment. Essays on New Resources in an Urban Age. Washington: Resources for the Future, Inc. Pickard, J. 1971. U.S. Metropolitan Growth and Expansion, 1970-2000. Washington: Urban Land Institute Powell, A.T.R., ed. 1972. The City: Attacking Modern Myths. Toronto: McClelland and Stewart Pred, A. 1973. 'The Growth and Development of Systems of Cities in Advanced Economies,' in Systems of Cities and Information Flows. Lund Studies in Geography, ser. B, no. 38. Lund, Sweden: Gleerup

22

Urban futures for Central Canada

Resources for Tomorrow. 1961. Conference Background Papers. Ottawa: Queen's Printer Richardson, B. 1973. The Future of Canadian Cities. Toronto: New Press Royal Commission on Canada's Economic Prospects. 1957. Final Report. Ottawa: Queen's Printer Science Council of Canada. 1971. Cities for Tomorrow: Some Applications of Science and Technology to Urban Development. Report no. 14. Ottawa: Queen's Printer Systems Research Group. 1970. Urban Canada 2000. Toronto: SRG The Urban Institute. 1969. Urban Processes as Viewed by the Social Sciences. A National Academy of Sciences Symposium. Washington: The Urban Institute US House of Representatives, Panel on Science and Technology. 1969. Science and Technology and the Cities. Washington: The Urban Institute Vernon, R. 1960. Metropolis 1985. Cambridge: Harvard University Press Vickers, Sir G. 1971. Freedom in a Rocking Boat: Changing Values in an Unstable Society. New York: Basic Books Wilson, A.G. 1969. 'Forecasting Planning,' Urban Studies, 6: 347-67 Wilson, A.G. 1972. 'Understanding the City of the Future,' The University of Leeds Review, 15: 135-66 World Bank. 1972. Urbanization. Washington: IBRD World Future Society. 1972. The Futurist (A journal of forecasts, trends, and ideas about the future, bimonthly). Washington Yeates, M. 1974. The Windsor to Quebec Axis in a PostIndustrial Age. Montreal: McGill-Queen's University Press Young, M.E., ed. 1968. Forecasting and the Social Sciences. London: Heinemann

I

Forecasts of urban growth

Editors' comments The dialogue on social and economic forecasting has been long and continuous. Forecasts should be made, say the pessimists, only if no one takes them too seriously. Clearly, to predict the future accurately, at least for most activities in which man has the dominant decision-making role, is virtually impossible. What is commonly attempted is to outline a number of possible futures based on a set of alternative assumptions. The ultimate goal of such forecasting is to consider the desirability of each alternative within the context of explicit societal goals. The successful forecast is not judged solely by its accuracy when the time period does arrive, but on its functional use in the present. The criterion for judgment is the use to which a forecast is put rather than whether or not it scores a bull's eye in prediction. Three of the four papers in part I present a range of forecasts of the future environment of Central Canada. A valid and well-thought-out forecasting procedure must specify the set of assumptions and premises from which it derives and the objectives it is trying to attain. The first paper discusses some of the basic assumptions and premises that the forecasts in the remaining three papers rest upon: the definitions of the spatial dimensions of the study area and the stability of population growth among urban areas in

24

Urban futures for Central Canada

Central Canada. In this paper Simmons and Bourne find that the urban system has been remarkably stable in terms of relative population size over the past century. There has been a tenfold change in size, but the growth rate has remained regular, and the relative position of urban places in Central Canada has remained largely unchanged. This is encouraging for the interpretation of the forecasts presented in the three following papers. If growth in the past has consisted largely of a change in scale which has not drastically altered the relative structure of the urban system, the likelihood that the current forecasts are relevant is increased. Indeed the authors conclude that the future seems to be 'more of the same,' a context which greatly facilitates the use of these forecasts in subsequent sections as a basis for speculation on other components of the future urban environment. Forecasting populations for small areas poses some fundamental philosophical problems, as is pointed out in paper 2 by Curry and Bannister. The authors adopt an apparently simple problem - forecasting the populations of townships in Ontario - as a starting point for a sophisticated investigation of the limits of prediction for small-area data of this kind. The forecasts,presented in detail in appendix A, provide useful estimates of the spatial distribution of Ontario's future population. One of the objectives of this volume is to assemble in one location recently published population forecasts for cities in Central Canada. Appendix B presents the forecasts which were obtained and their varied sources as well as those forecasts derived from the Urban Environment Study itself. Paper 3 by Siegel then discusses the methodology and techniques used in generating these forecasts and presents a summary table giving the high, medium, and low forecasts for each city. This table provides a good indication of the range of alternatives for growth of the urban areas in Central Canada and the effects of differing assumptions. The high and low forecasts, for instance, reveal the importance of migration assumptions in forecasting population growth at the aggregate urban system level. They account for most of the spread about the median. Paper 4 by Miron applies these population forecasts to predict employment growth by industrial sectors for the metropolitan region of Toronto, a ten-sector summary of which is presented in the paper. A two-phase method is used to

Defining the future urban system

25

generate the forecasts: first, a national employment forecast is obtained; then a regional share of that growth is forecasted. From these two series it is possible to obtain a forecast of urban employment by each industrial sector. Miron's study reveals some interesting divergences between the employment growth nationally and regionally for Toronto. Nationally there is forecasted a shift in the component of Gross National Expenditure away from foodstuffs and manufactured goods towards rents, home ownership, travel, and personal services - in general a shift from 'hard1 goods to 'soft1 services. However for Toronto Miron finds that it is forecasted that the employment share of manufacturing is to increase. This seems to contradict the conventional wisdom which views the metropolitan regions as increasingly centres of activity in the service sector. He concludes that the historical dominance of manufacturing within the Toronto region will continue. The papers in this part present the methodological and empirical foundation for a look into the future of Central Canada. The numerical forecasts presented in these papers provide a range of alternatives upon which the following two parts in this volume build. Part II explores the regional interconnections of the urban areas in Central Canada: the relationships between the urban hierarchy and growth, and the migration and transportation linkages. The papers in parts II and III explore hypotheses, present information, and discuss policy issues which may and almost certainly will act to change the forecasts presented in part I. The reader is urged to utilize the materials in these sections to modify the forecasts presented in this part according to his own intuition and biases concerning the urban future of Central Canada.

1

Defining the future urban system JAMES W. SIMMONS and LARRY S. BOURNE The Urban Environment Study examined the future forms of urban development in southern Ontario and southern Quebec a region designated as Central Canada.1 Within this general

26

Urban futures for Central Canada

spatial framework, however, a wide diversity of definitions of the urban system has been used as a result of the varied interests, purposes, and data sources of the researchers involved. Because many of the results and forecasts are closely related to the area and units of observation, it seems appropriate to recapitulate some of the spatial and temporal dimensions of the studies presented in this volume and the issues which were considered in deciding on what definitions to use. THE STUDY AREA The region designated as Central Canada varies according to the main data set used in each component study. The primary area of concern (the urban core) corresponds essentially to the St Lawrence-Great Lakes corridor stretching from Quebec City to Windsor (see frontispiece). A secondary area included in some analyses encompasses the resource exploitation cities extending north on the Laurentian Shield. The two areas exclude a large proportion of the land masses of the two provinces of Ontario and Quebec but include over 90 per cent of the population and economic activity, and virtually all the foreseeable areas of major growth. Many of the early studies based on census measures (Bourne and MacKinnon, 1972) included all cities or metropolitan areas within the two provinces, but some later analyses drawing on other data sources delete most of the cities in the area of secondary concern. Since the latter cities are differentiated in terms of their economic base and their accessibility to the rest of the urban system, analytic results and insights may be quite different. Studies including the northern ring of cities, for example, suggest a dimension of staple-based economies linked to high-order service centres in the main urban corridor. Studies examining the cities of the main corridor alone describe a complex and highly industrialized urban economy with a wide variety of linkages based on economic specialization as well as size and accessibility. As the individual component studies evolved over time, the initial casual concern with a politically bounded urban system consisting of the provinces was partially replaced by an interest in the actual pattern of system linkage. Can a partially closed system or set of subsystems in Central Canada be defined to include most of the regular contact

Defining the future urban system

27

patterns of the corridor cities? Can the origins of the forces of growth and change be located within such a subsystem? The difficulty, of course, is that information on patterns of interaction, or interregional growth multipliers, is extremely difficult to obtain. The most useful approach, from the perspective of hindsight, would be to make the study area coincident with two urban subsystems - one dominated by interaction with Montreal (including Ottawa), and one by Toronto. Fortunately their service hinterlands closely approximate existing political boundaries (see frontispiece). The international border effectively bounds both regions to the south, acting as a major deterrent to the easy flow of migrants, customers, goods, and services. Windsor is a possible exception, as it is obviously more closely linked to the Detroit region than to Toronto in many ways. The eastern and western boundaries of the study area are also fairly straightforward. Simmons and Simmons (1969) have suggested the effectiveness of provincial boundaries in defining metropolitan regions, although the WinnipegToronto boundary probably lies between Thunder Bay and Kenora. It can also be argued that Winnipeg, Edmonton, Vancouver and indeed Halifax - are subservient to Montreal and Toronto for certain functions; and hence are part of the same system. The counter argument is that the higher-order relationships for these cities are diffuse and shared among several places, not directly linked as are the cities in the subsystems defined here. The rural-urban boundary The urban system is further bounded by the implied differentiation between urban and rural areas, in that the analysis focuses on the sixty to seventy urban regions in the two provinces containing 70 or 80 per cent of the population. Initially an explicitly rural component to the Urban Environment Study was proposed, but eventually this research was replaced by a growing concern with the effects of urban areas on the rural landscape (paper 15). For the most part, however, the analyses describe the cities and metropolitan areas as defined in the 1961 Census, a rather small proportion of the total land area even in the primary area of concern. Again certain specialized analyses were undertaken on smaller nodes, within a smaller region. Paper 2 by Curry and Bannister is most useful in linking together the changes,

28

Urban futures for Central Canada

past and future, of all components of the landscape. As the discussion of various forecasts of metropolitan areas (paper 3 below) suggests, however, any study of the urban system oriented towards the future requires a more flexible approach to the question of urban boundaries. Definitions of a city which are currently valid overbound cities of the past and underbound cities of the future. Since the peripheral areas of cities are the zones of the most intense growth, severe distortions may result. Again some solutions are put forth ex post. Simmons and Bourne (1972) argue that several widely varying definitions of 'Toronto1 or any other city exist simultaneously, permitting analysis to take place at several levels at once (figure 1.1). Alternatively one can move to a system of functional urban regions (Fox and Kumar, 1965; Berry, 1968) which cover the entire study area. Thus rural areas are aggregated with the urban node that serves them. Not only does the rural-urban boundary become irrelevant; the urban region which results provides a better measure of the city's economy. Rural service centres include an explicit agricultural sector, and analyses of regional economies are not affected by shifts from primary to service occupations within the region.

Area (sq miles) Figure 1.1 Definitions of Toronto

Defining the future urban system

29

The definitional issues cannot be fully resolved. Data and analytical constraints compel different authors to deal with the problem in their own ways. Throughout this volume, however, the discussions have been made as spatially explicit as possible. THE HISTORICAL CONTEXT OF THE SYSTEM The hazards of forecasting will be stressed repeatedly throughout this volume. Unanticipated changes in technology, in policy, and in people's preferences, as well as even modest shifts in fundamental growth parameters, have had profound impacts on the form of urbanization over a generation and a half. The difficulties are never more evident than when the record of the last century is examined. Since 1850 the urban system in Central Canada has grown by a factor of ten; it has responded to three or four diverse technologies and adapted to a radically different continental geography. The amazing response of the system, and a fundamental premise for the remaining studies in this volume, is one of great stability over time. The growth rate has remained regular, and the relative sizes of urban places are largely unchanged; only the scale is altered. Table 1.1 demonstrates the stability of relative size patterns in Central Canada from 1851 to present. The upper echelons of the hierarchy - as defined in 1871 - are very consistent in relative size. Much of the variation in later years, as measured in lower correlation coefficients, is the result of random fluctuations (often due to measurement difficulties) at the lowest level of the hierarchy. The evolution of the urban system One's faith in forecasting is strengthened by a consideration of the diversities of environmental contexts which have been served by the same urban system. Sites identified in the era of the fur trade have continued to serve as service centres within agricultural regions, as manufacturing centres, and now as components in a complex metropolitan system. Two themes in urban history rationalize this stability. The first theme is drawn from the notion of the staple-oriented economy, still relevant to large parts of Canada, including the 'area of secondary concern1 in the frontispiece and much of the earlier (before 1880) pattern of Central Canada. The second theme describes the growth

30

Urban futures for Central Canada

TABLE 1.1 1 Correlations of population rank, Central Canada, 1851-1971

Year

Number of cities

1851 1871 1891 1911 1931 1951

5 9 14 27 42 52

1851

1871

1891

1911

1931

1951

1971

1.00

1.00 1.00

0.90 0.99 1.00

0.65 0.98 0.98 1.00

0.65 0.97 0.98 0.93 1.00

0.65 0.97 0.98 0.84 0.91 1.00

0.70 0.82 0.90 0.73 0.94 0.92

The parameter is Spearman's rank-correlation coefficient. Rankings of all cities over 10,000 at a given date are compared at later points in time. The 1851 set, for instance, contains only five cities: Montreal, Toronto, Quebec, Hamilton, and Kingston.

of cities dependent on an industrial base - the source of most of the recent growth in the Great Lakes-St Lawrence corridor. Throughout the sequence of staple economies in Central Canada - from furs, to timber, to wheat, to the pulp and paper or mining towns of the shield at present - the rapid fluctuations of the peripheral economies are translated into stable continuous growth in the high-order corridor centres which provide services for the system. A decline at Elliott Lake, for instance, is replaced by a surge of growth in Timmins; Toronto prospers either way. Not all staples are widely unstable either. The agricultural economy is extremely flexible and in Central Canada has been able to adapt continuously, forming a stable basis for a number of regional service centres, e.g., London, Sherbrooke, Chatham. In any event very early in the settlement sequence the basic networks of strategic situations were identified; and these have remained significant throughout the series of economic, social, and political environments which followed. Towards the end of the nineteenth century an industrial economy was superimposed on the above, developing from the staple production (Gilmour, 1972), and then from the existing urban system; but also from a new role for the whole region providing the rest of the nation with manufactured goods and

Defining the future urban system

31

commercial services. Pred (1966) and Thompson (1965) suggest the inherent sources of stability in a manufacturing economy: the advantages of various economies of scale and localization, the sources of capital and innovation, and the power to control infrastructure investments. Although some new centres crashed the higher order (e.g., Windsor, Oshawa, Drummondville), most of the new growth occurred in the larger cities as before. Patterns of growth in the early twentieth century are essentially system-reinforcing. The last twenty-five years have seen the development of a new aspect of urbanization - the metropolis. Toronto and Montreal are reaching out, merging with and polarizing the areas around them. Differentiation between urban and rural is increasingly arbitrary. The economy of Central Canada is almost entirely urban and closely integrated. THE FUTURE URBAN PATTERN Numerous authors, for instance Berry (1970) and Morrison (1972), have attempted to anticipate the future form of the urban system in the United States. They portray a nation almost completely urbanized, its geography dominated by enormous interlocking urban fields. These fields represent commuter and recreational 'sheds' for the major metropolitan complexes and envelop virtually all of the inhabited area of the country. However the most dynamic growth in the remaining years of this century is expected to occur at the boundaries of the urban fields - the interstices between metropolitan areas rather than in the metropolitan regions themselves. These interstices are at present the backwater problem regions of the country - areas receiving government economic assistance. The urban geography of the United States in the year 2000/ they argue, may turn itself inside out. The old urban cores appear to show an irreversible decline in terms of population mix and in the intensity of economic activities. Even the suburbs will lose out as population spreads further and further out into the recreational hinterland in a highly competitive search for space, privacy, and peace. The Canadian context Lithwick (1970), MacNeill(1971), and others have attempted a similar exercise for Canada. To some extent the futuristic images in Canada are much less dramatic: a more modest

32

Urban futures for Central Canada

helping of 'more of the same1 is indicated. The massive and rapid social and geographic change anticipated in the US urban situation is not proposed by many serious observers of the Canadian scene. No degree of urban growth yet anticipated in Canada will occupy more than a thin band of land along the countryf s southern border (nevertheless it should be noted this includes virtually all of the national living space or 'ecumene1). Canadian cities will demonstrate less drastic internal changes in form than their US counterparts. Cities in this country have been capable of a great deal of selfrenewal; they are dispersing and growing outward, yet they are also experiencing increases in central density as well. The 'doughnut'-shaped model of the future American metropolis with a depressed region in the centre, as proposed above, is not applicable to urban regions in this country. Perhaps the major source of concern about the urban future of Canada is some variation on the themes of 'regional disparity1 or 'metropolis unbounded.' It appears likely that the two major metropolitan areas, Toronto and Montreal, will continue to grow much more rapidly than the rest of the country - absorbing the lion's share of new capital investment and infrastructure - a critical problem within a small and thinly populated nation such as Canada. To an increasing degree they are polarizing the national economic landscapeaffecting land uses, capital investment strategies, and other regional economies through their market influence and financial control (Kerr, 1968). Politically and culturally they are creating new Canadian urban images and generating new policies which tend to obliterate or ignore the cultures, values, and independence of other places. This is the main issue which seems to lie behind most discussions of an urban policy at the national or regional level. Reactions to this issue may also provide the key to an understanding and appreciation of the form of urban Canada in the remaining years of this century. NOTE 1

This terminology is not original; see Ray and Berry (1965).

REFERENCES Berry, B.J.L.

1968.

Metropolitan Definition:

Reevaluation

Defining the future urban system

33

of Concept and Statistical Practice. Working Paper no. 28. Washington: US Bureau of the Census Berry, B.J.L. 1970. !The Geography of the United States in the year 2000,' Transactions of the Institute of British Geographers, 51: 21-51 Bourne, L.S., and MacKinnon, R.D., eds. 1972. Urban Systems Development in Central Canada: Selected Papers. Toronto: University of Toronto Press Bourne, L.S., MacKinnon, R.D., and Simmons, J.W., eds. 1973. The Form of Cities in Central Canada: Selected Papers. Toronto: University of Toronto Press Bourne, L.S., and Simmons, J.W. 1973. fThe Area of Interest: Urban Definitions in Canada,' in L.S. Bourne, et al., eds., The Form of Cities in Central Canada: Selected Papers. Toronto: University of Toronto Press Fox, K.A., and Kumar, T.A. 1965. 'The Functional Economic Area: Delineation and Implication for Economic Analysis and Policy,' Papers, Regional Science Association, 15: 57-85 Gilmour, J.M. 1972. The Spatial Evolution of Manufacturing: Southern Ontario, 1851-1891. Toronto: University of Toronto Press Kerr, D. 1968. 'Metropolitan Dominance in Canada,' in J. Warkentin, ed., Canada: A Geographical Interpretation. Toronto: Methuen. Pp 531-55 MacNeill, J.W. 1971. Environmental Management. Ottawa: Queen's Printer Morrison, P.A. 1972. 'Population Distribution Policy: Issues and Objectives.' Paper presented to the annual meeting of the Population Association of America, 13-15 April 1972 Pred, A. 1966. The Spatial Dynamics of United States Urban and Industrial Growth, 1800-1914. Cambridge: MIT Press Ray, D.M., and Berry, B.J.L. 1965. 'Multivariate SocioEconomic Regionalization: A Pilot Study in Central Canada,' in S. Ostry and T.K. Rymes, eds, Papers on Regional Statistical Studies. Toronto: University of Toronto Press. Pp 75-122 Simmons, J.W., and Bourne, L.S. 1972. 'Toronto: Focus of Growth and Change,' in R.L. Gentilcore, ed., Ontario. Studies in Canadian Geography 3. Toronto: University of Toronto Press Simmons, J.W. and Simmons, R. 1969. Urban Canada. Toronto: Copp Clark

34

Urban futures for Central Canada

Thompson, W.R. 1965. A Preface to Urban Economics. Baltimore: Johns Hopkins University Press

2

Forecasting township populations of Ontario, from time-space co variances LESLIE CURRY and GEOFFREY BANNISTER

There is a history in all men's lives, Figuring the nature of the times deceased; The which observed, a man may prophesy, With a near aim, of the main chance of things As yet not come to life, which in their seeds And weak beginnings lie intreasured, Such things become the hatch and brood of time. King Henry IV, Part II, Act III, Scene 1 For we are all, like swimmers in the sea, Poised on the top of a huge wave of fate, Which hangs uncertain to which side to fall, And whether it will heave us up to land, Or whether it will roll us out to sea, Back out to sea, to the deep waves of death, We know not, and no search will make us know; Only the event will teach us in its hour. Matthew Arnold, 'Sohrab and Rustum,' 1853. THE FORECASTS Rationale Now in the early 1970s we want to draw a map, by townships, of the population of Ontario in 1981, another map for 1991, and again, even more tentatively, a map for the year 2001. It is certainly easy enough to write down sets of numbers and draw maps, but we must also convince ourselves and our readers that our methods and our results are reasonable. We have surveyed the literature (Curry, 1970) and made in-

Forecasting township populations

35

numerable experiments in choosing a method: the technical aspects of the latter are outlined in later sections of this paper. As an immediate and a minimum preamble to the presentation of the results, we here discuss the main problems involved in this type of forecasting. The quotations from Shakespeare and Matthew Arnold above present the basic dilemma of all prediction. History is the hatch and brood of time; the future is unknowable: our task is to seek out those components of those sequences which show some ordering, test whether this ordering allows prediction at an acceptable level of accuracy, and assume that this ordering will continue into the future. Each event is regarded as an amalgam of the unforeseeable, the independently random inputs, and of an ordering principle, some space-time relation between inputs. Clearly the further we look into the future, the more we must permute probabilities and the more the system takes on an independently random character; predictability decreases. Ordering is largely a function of classification. History can legitimately be regarded as a series of unique events. In 20 years unforeseeable inventions will be made and adopted, major locational decisions made, and new regional policies put into operation. On the other hand, technological change has occurred throughout history and government policies have always been present. From a broad enough viewpoint changes are in intensity and not in kind. If some ordering can be ascertained over the period of the census-recorded past, why should we expect it to change in the near future? It nevertheless lies within the power of governments to change completely the economic map of Ontario and so totally to falsify a forecast based on past trends. It is possible for governments rapidly to establish a large and viable industrialcommercial complex where presently there is very little development, indeed in a place which is low in comparative advantage vis a vis other undeveloped places. However the implementation of a policy to achieve these ends would be such a radical political departure from anything seen in the western world heretofore, and from any existing political and social trends in Ontario, that it must be regarded as having a very low probability of occurring. There is a tremendous conservatism in the ways that such a basic property as the distribution of people over territory changes. Each person's decision which might affect the map are a small part of the whole and are profoundly affected

36

Urban futures for Central Canada

by the present structure as a going concern: decisions are not taken simultaneously, and personal and institutional investments are only slowly amortized. Changes do occur, but they must be related to what is going on elsewhere; they will be based on individuals1 views of the future, and these views will be based on what has happened in the past: thus time trends in map changes develop. This explains why, although population is being forecasted, we do not consider the usual determinants such as fertility and mortality. Methods using these variables are best suited to aggregations over large areas so that internal migration is of little importance. Because the map of population is required, migration assumes overwhelming importance as a demographic variable. We should thus look for the determinants of immigration or emigration in small areas. This leads us to examine the way in which the populations have changed in the past as an index of their future attractive or repulsive power. Consequently past performance, which includes the best estimates of current changes, is likely to provide a reasonably reliable viewpoint on the future. Interaction between people and the movement of people always has been and presumably always will be affected by the friction of distance: as well as direct transport costs, there are also limitations on the extent of information flows, including here fields of habitual social contacts, on the willingness to commute or migrate. New transportation facilities may alter the distribution and intensity of these frictional effects, but they are related to the present character of the distribution and particularly to changes in it. Adaptive behaviour between accessibility and changes in population numbers is generally slow. Consequently there are likely to be discoverable empirical relations between the time derivatives of population in different areas because they have been affected throughout by the same spatial interactions. If irregular developments occur - the inital establishment of Ottawa as a national capital is an obvious case in point - the numbers involved are usually small and the inability to forecast them not too serious. Once the census has picked them up a couple of times, empirical relations between changes elsewhere and the way in which the Ottawa area develops become established, and forecasts can be made. Basically, what we assert is that the economy exists as a complex spatial structure and changes occur taking this structure into account.

Forecasting township populations

37

Spatial forecasting Spatial forecasting should depend entirely on our understanding of how the society and economy operates in its own area. Given a reasonably adequate theoretical structure, questions concerning data manipulation could be rationally examined; given good enough theory, we might not even need any data. We can only agree and admit without fear of contradiction that there is no theory, not simply inadequate but zero theory, to handle this sort of problem. Even intuition fails on most occasions to guide one's choice of procedures. Forecasting in the matters of concern here is purely an art. The various equations used below should not be read as reflecting any scientific basis for the work. Given the goal of a population map of Ontario for 1991 and 2001, the paucity of data, and the lack of any relevant theory, the only approach possible is a numerical one, based on a few weak intuitive ideas. The only sop to the scientific conscience is that methods are stated unambiguously and attempts are made to check the results of these methods. Even these apparently minimum requirements are found in only a few forecasting schemes. The essence of spatial forecasting is that temporal variation in a township is very much influenced by what is going on elsewhere. If we can read how the time path of development of a township has been influenced by previous development elsewhere, we have a basis for prediction. A general method for doing this is to decompose a map into scale components, produce a time series for each component, forecast the future of each scale component on the basis of the temporal ordering discovered, and then reassemble the composite future map. Another method is to seek lag regression relationships either with nearby townships or with 'indicator * townships. The method used here is a combination of these two approaches. Essentially we group townships into regions of increasing scale and obtain a number of maps which describe the contribution of all scale components to the initial township map. If we do this for a set of successive census maps, we can investigate how the scale components change with time and how changes in a township are related to previous changes in various larger-scale components. Given the many types of spatial change which can occur, this method appears to be comprehensive while leaving open many options for choosing, on an empirical basis after experimentation, which relation-

38 Urban futures for Central Canada ships should be employed. In the time series mode of forecasting we try to choose a middle course between designing a prediction operator to respond rapidly to changes in direction and making it sufficiently stable not to respond to impermanent changes which are not followed up. The method we use involves taking the first and second time differences back, from the most recent year, for each scale component of a township's regional hierarchy. We are revealing how these regional components are changing, constrained by their most recent past. We now need to weight these differences in order to estimate the change that will occur for the following period. We do this by choosing coefficients which best describe how changes through a township's history were related to immediately preceeding first and second differences at each hierarchical level. Operation of the forecast scheme The development of a region will depend on development going on elsewhere. Ability to grow relatively is proportional to the ability to draw in labour and thus occurs at the expense of other regions. For a region to show large growth some neighbouring regions must have negative time differences. As well as this competitive effect for labour, which results in opposite signs in differences, there is also a similarity effect. If a number of neighbouring areas grow together, we must assume that there is some form of spatial contagion effect or alternatively that the areas are reacting similarly to some common stimulus. It will show up by having opposite time differences only at higher hierarchical levels where competitition for labour must be occurring. The spatial scale of the differentiation of time differences, will, of course, depend on the time periods involved, whether labour availability is to depend on the willingness of persons to come on the labour market, the willingness to commute, the willingness to migrate. It will also depend on all the various spatial frictions involved: the extent of space search in seeking alternative locations, the spatial extent of information flows, and so on. The actual working of the forecast scheme does capture the essence of the space-time economy: we see Ontario evolving far from simply up to the year 2001 in a truly dynamic fashion. The complex interactions of the scale components are often beyond simple intuitive grasp, so that the predicted course of development cannot be anticipated or even

Forecasting township populations

39

understood without a detailed tracing back of what is happening in many different areas at different times. Although we cannot really justify any particular forecast, the results do look remarkably reasonable. Of course this reasonableness is partly an artefact, since we choose predictor variables partly on the basis of the reasonableness of their predictions up to 1981: we are choosing predictor variables only because we do not have sufficient data to employ all the variables available to us. Nevertheless we could not necessarily expect sensible answers up to 2001. Apparently the scheme we have so laboriously developed is working as we wished; it has incorporated both the stability and the flexibility we aimed for and it is reflecting the naive notions of process which guided its design. Before going on to examine the results, one word of caution is required. The whole emphasis has been on forecasting the individual township's population from knowledge of its lagged relation to development going on elsewhere. We can and have totalled the township values to report forecasts for the whole area (table 2.1), but are somewhat ambivalent as to their accuracy - they might be low. It seems likely that forecasting at the provincial level could be done in a much more sophisticated fashion using many more factors, both interprovincial, national, and international, to achieve more reliable results. Our forecasts are best regarded in relative terms as spreading the provincial total of future years around the province. However our forecasts, even on an absolute basis, do not seem unreasonable. TABLE 2.1 Total population for southern Ontario, 1951-2001 Year Population (in OOOs) Change (%)

1951

1961

1971

1981

1991

2001

4,057

5,556

7,046

8,111

9,284

10,967

36.9

26.8

15.1

14.5

18.1

The final results from the forecast procedure are presented in appendix A. Figure 2.1 shows the spatial aspects of the growth and decline trends in township populations deriving from these forecasts.

Figure 2.1

Forecast of population change, 1971-2001 (per cent)

Forecasting township populations

41

Size changes Three major trends are evident in the forecasts based on the original township division: 1 a gradual decline in the townships with low populations; 2 a pattern of increase around the mean for townships in the middle size range; 3 strong, sustained growth in both absolute and relative terms for the largest areas. A projected decline of small townships is evident from table 2.2. There is a general decrease in the proportion of the population living in townships with fewer than 10,000 people. For townships with fewer than 5000, the decline occurs in absolute as well as relative terms (table 2.3). There is also an interesting pattern of change in the number of townships in each size group (table 2.4), with a steady increase in those in the 1000-5000 category. Presumably some form of filtering between size classes goes on in which those townships with a weak competitive location move down a class, while the others maintain their position or move up. As the weaker members filter down, the pattern stabilizes to a well-defined cluster of decreasing townships in the 0-1000 class and increasing areas in the 1000-5000 category. TABLE 2.2 Township size groups and percentage of total population, 1971-2001 Township population (in QOOs) 0-1 1-5 5-10 10-25 25-50 50-100 1971 1981 1991 2001

0.6 0.5 0.4 0.3

8.1 6.3 4.9 4.1

8.5 7.6 6.9 5.9

6.3 7.6 8.0 7.8

11.1 10.4 8.9 8.7

10.5 7.8 9.4 10.5

100-30C) 300+ >25 21.8 24.4 20.2 15.6

32.9 35.3 41.3 47.0

76.3 77.9 79.8 81.9

Of the township categories contained within the size range from 10,000-300,000, only the 10,000-25,000 group shows an increase in the number of towns or in the proportion of the total population they contain, although all of them record absolute gains. The increments to the 10,00025,000 range reflect the movements of the stronger townships that have filtered up from the size classes below.

TABLE 2.3 Township size groups and associated populations, 1971-2001 Township population 5-10,000 0-1000 1-5000 1971 1981 1991 2001

44982 43409 36193 30076

571266 511836 460417 450206

601384 616552 641774 646799

10-25,000

25-50,000

50-100,000

100-300,000

300,000+

TOTAL

445966 613712 741131 853180

785992 841141 824555 957202

741376 635126 870346 1157112

1536527 1981230 1877882 1716023

2318840 2867785 3831493 5153602

7046333 8110791 9283791 10966900

TABLE 2.4 Number of townships by size group, 1971-2001 Township population 5-10,000 0-1000 1-5000 1971 1981 1991 2001

85 94 105 106

225 202 175 162

86 88 91 87

10-25,000

25-50,000

50-100,000

100-300,000

300,000+

30 41 49 58

24 24 24 27

11 9 13 16

9 11 10 9

5 6 8 10

Forecasting township populations

43

The strongest growth is forecast for those townships with over 300,000 people, the core areas of metropolitan regions. It is evident that urbanization is continuing, and most of this movement is concentrated in the already densely populated regions. There is an increase not only in the number of township divisions with more than 300,000 inhabitants, and in their absolute populations, but also a strong increase in the proportion of the total population they contain. Through each of the decade forecast intervals, all of these townships show positive growth rates, with the majority of them above average. Regional changes No single-factor explanation can adequately account for the process of change in the forecast maps (figure 2.1). The result is clearly some complex integration of city size, hierarchical ordering, and regionalization effects. In the south, around the major metropolitan areas and on the Niagara peninsula, growth is generally strong in both relative and absolute terms. Part of the explanation is simply that larger cities are more likely to grow, but there is also a strong interdependency effect evident from the areal cascade values. Most townships in the 'horseshoe1 benefit from growth on the part of their neighbours, with development diffusing from the poles of growth. However in the more northerly townships, and especially in Muskoka county, growth is not only slow in the aggregate but also polarized. Here the growing townships are usually surrounded by stagnating or declining neighbours, and in nearly every case the growing centres are the larger ones. Thus the advantages of city size vary from region to region. In the slow growth areas size appears to be one of the few salvations, but in the more prosperous south townships can also benefit from proximity to growing neighbours. The major growth stimulants, therefore, seem to be size, centrality, and interdependence, trends that serve to increase slightly the population dominance of the south. Around the western end of Lake Ontario the counties of Ontario, York, Peel, Halton, Wentworth, and Lincoln increase their combined share of the total population from 50.2 per cent in 1971 to a projected 51.2 per cent in 2001. The declining areas are usually distant from this core, in Huron County in the west, in Muskoka and Parry Sound to the north, and Russell, Stormont, Glengarry, and Prescott counties in the east.

44

Urban futures for Central Canada

TECHNICAL DISCUSSION Experiments with the time structure General we are seeking a form of space-time ordering for prediction purposes, but we can discuss time changes on their own at this stage. The most naive method would be to fit a mathematical expression such as a polynomial to the census series with absolute time as an argument and extend the curve so fitted into the future. Each value is given equal weight, and it is obvious that the curve may not pass through the most recent observations. Essentially we would be assuming that some form of absolute momentum, acquired from all the past, is being projected into the future. The polynomial is fitted over the whole series synoptically; literally all observations are affected by a single noise distribution. One could interpret this as the values in each period being affected by identical noise distributions, but the mechanism generating the 'true1 values is unspecified (since the order of polynomial required to provide a good fit cannot be given a priori). Nevertheless it operates as an irrestible force from the beginning of the record. It is probably this form of projection to which critics refer when they speak disparagingly of trend-fitting. It is virtually impossible to discuss a process in substantive terms; no constraints exist for relating sequential values. The alternative view is one of the value of a township in, say, 1970 being the result of its value in 1960 plus the derivatives which exist at that time, or, what is almost the same thing, plus the values in 1950 and 1940. The future is thus discerned on the basis of changes in the most recent past. Values in all periods are regarded in the same way. The object of the statistical exercise is to determine how much we should weight the various derivatives of the preceeding year in order to 'explain' the current year. We are thus assuming that the influence of the various derivatives are constant through time; the derivative is not constant, but the weight we attach to it is. The weights are chosen to best fit the recorded series, implying identical noise distributions for each period. Autoregressive process: Stationary overall Our first program is concerned with time variation and does not consider spatial aspects. The object of the program is to investigate

Forecasting township populations

45

what could be done with very short series, and tests were made using artificial series of about ten values. The criterion of the tests was how well later values which were not used in constructing the scheme were forecast. Some methods also allowed comparison of values generated by the scheme with the values which were input to it. One of the main purposes of these investigations was to gain insight into the adaptability and flexibility of the equations and how these were affected by the fitting procedures. Initially we chose an autoregressive process, stationary throughout,

with the linear predictor

Coefficients were calculated for a predetermined order of equation, and we also allowed the fitting scheme to determine the order (Jenkins and Watts, 1968; Curry, 1971). We had little optimism for the success of this model, since it cannot be used when a series has continually increasing values for example. We did hope that, if we initially subtracted low-order polynomial components so as to render the series stationary, it could be used. However it rapidly became apparent that, with our short time series, the polynomials were taking up most of the variance so that it was doubtful whether the procedure was justified. As well as having a jungle of coefficients, we were combining the lowest possible form of extrapolation with a highly sophisticated probabilistic forecast. Autoregressive process: Stationary for fixed time span The previous work showed that a second order process was likely to be adequate. We now relaxed the requirement of stationarity somewhat by requiring it only over six consecutive values of eight data points. Assuming an overall mean of zero, the normal equations to be solved are:

46

Urban futures for Central Canada

where

and all summations extend from t = 4 to t = N. It may be seen that *txt-l is differentiated from *t-lxt-2 so that the process is not fully stationary. This is a stochastic model with which we hoped to obtain probability forecasts. However it was not sufficiently flexible to follow curves defined over a few data points. Empirical difference equations as

Writing the autoregression

{2} Although these equations and those below are difference equations, we shall refer to those above as weighted past values and reserve 'difference' for changes in values between periods. In the Z transform form it is clear that we could substitute differences rather than actual values to obtain a different but, in this form, similar type of equation. Writing A72 for the difference operator and substituting it for Z~n and b± for a±/

{2} Since finite differences are used, it is always possible to define the AS in terms of the actual values. Given that A = second order equation may be written.

{3} This is much the same equation as equation 1 save that the a^s of that equation are not necessarily interpretable as differences and equation 3 requires only two coefficients compared to three if written in the form of equation 1. It

Forecasting township populations

47

may also be noted that, while equation 2 is written as a stochastic process, there is no necessity to assume it stationary. It would be a 1, 2, 0 process in Box and Jenkins terminology, save that we do not even wish to assume stability. All that we require is that the various orders of differences can be averaged in a root mean square sense to produce estimates of the coefficients for forecasting purposes. Usually economic and social spatial data from censuses would not provide sufficient time cross-sections to allow stationarity to be forced by the use of successive differencing a la Box and Jenkins. The form of any time series from cascading (to be discussed later) is not known, and indeed we must anticipate all possible forms: there will be hundreds and perhaps thousands of time series for a single map if we are to forecast future maps in considerable spatial detail. Some series could meet the tests of stationarity and some might not; some could take all positive values or all negative values or be a mixture; change could be slow or rapid. We wish to treat deterministic and stochastic components in a unified fashion as parts of a single general process of change while allowing the data to suggest the process as far as possible. To treat them separately appears absurd, given the shortness of the time series likely to be available, and prodigal in the number of coefficients generated, given the number of such series. However we are no longer describing a process in a meaningful mathematical sense and must incur the penalties. This has to do with forecast probabilities to be discussed later. Flexibility and stability There are two elements involved in the design of a forecast equation so far as operation in time is concerned: stability and flexibility. Since these tend to present conflicting criteria, some compromise is necessary. A single time series can be forecast by

The as are empirically determined coefficients which are obtained by least squares solution of the normal equations formed from past data. If one had, say, seven past observations and only wanted to calculate aj, one could form six equations and the least squares estimate would be statisti-

48

Urban futures for Central Canada

cally reliable in the sense of having a reasonable number of degrees of freedom. The forecasts would be relatively stable in the sense that there has been a fair degree of least squares averaging performed to obtain them. If one wishes to use a two-period lag, it is necessary to estimate a^ also. Clearly the number of equations to be used declines, and thus the stability of the estimates. The foregoing suggests that we should aim to keep the equation as short as possible to provide stability. However there are good reasons why it should be kep long enough to provide flexibility. It would seem to be necessary, for example, to have an equation which, while forecasting say an upward trend for a period, might then begin to decline. There appears to be something fundamentally unsound about a forecast procedure which in forecasting several steps into the future can only keep on going up or keep on going down. The obvious method here is to use two or more differences as in equation 2. The design criterion is to have an operator which will follow the curves of a series: it should be sufficiently fast-acting that it follows quite well, but at the same time sufficiently stable that it does not follow noise impulses. This shows up clearly when we test forecasts for both one period ahead and two or more periods ahead. In general, faster-acting operators tend to perform better for one period ahead, whereas slower-acting operators are better for longer periods into the future. We say 'in general1 because results will clearly depend on specific series. One method which should help to solve this problem is to reduce the influence of the older data in fitting the coefficients. They provide some influence, thus contributing to stability, while the reduction of their influence aids flexibility. This is the statistical counterpart of the reasonable belief that modern conditions are more important than early times in mirroring the modes of change which are to provide the future. Consequently, we introduced a 'forgetting function1 with a set or prearranged weights decreasing with age of the data. These weights must be chosen a priori since we have insufficient data to resolve them statistically: in fact we tried various exponential declines. However our results caused us to reject the notion of a forgetting function. The greater the discounting of past data in fixing the coefficients, the more volatile is the forecast, and thus the more capable it is of being sent

Forecasting township populations

49

off rather wildly by 'noise1 components. The impossibility of probabilistic forecasting We went to considerable length to obtain our forecasts in probabilistic terms, but have failed to do so. Again it was the length of record which defeated us. Initially we attempted to use a definite process model with an autoregressive structure: this has the considerable virtue that the scatter of the observation obtains a natural probabilistic interpretation. The 'errors' in fitting become a measure of the variance generated by the stochastic mechanism. Since this model proved too inflexible to follow curves at all well, we next moved to empirical difference equations. Our idea was to use the variance around the fitted function as a measure of the forecast probabilities with a normal distribution assumed. This is not really legitimate since the 'errors,' and thus the probabilities, do not refer to individual forecasts, but rather to a collection of forecasts based on the particular methods employed. However even this method had to be abandoned, and we were forced into the methods we finally adopted: we have hardly any degrees of freedom remaining after the necessary coefficients are fitted, so that, even if we believe the changes are stochastic in nature, we limit ourselves to estimating the 'mean1 forecast values. The standard error of the regression in fitting the curve has no relation to how well the forecast operates. Experiments with time and space structure Spatial scale components We expect that the temporal variation of a township will be very much influenced by what is going on elsewhere. The spatial arrangement of the economic and social relationships between townships places considerable constraints on the possible paths of evolution of a township considered in isolation. In forecasting a whole map we must investigate and exploit the spatial arrangement of the temporal covariance of townships. We may do this by measuring the dependence of a township's population at some time on its past values as well as any covariance occurring on other townships chosen on a priori grounds (Cliff and Ord, 1971). Alternatively we may divide the map into a set of orthogonal components so that the map is described in standardized mathematical terms with empirically fitted coefficients. A sequence of maps provides a time series of

50

Urban futures for Central Canada

coefficients for each component from which forecasts may be made and the results added to produce the future map (Miller, 1967). In our series of experiments a particular form of the second method was adopted, but this was later amended to incorporate a form of the first method so that our final procedure is a hybrid. The components we seek to extract are those comprising different geographical scales of differentiation. One way of partitioning a map into scale components is by cascaded averaging and differencing (Curry, 1970). Given a population map of Ontario by townships, the mean population per township can be stated and for each quarter of the map the deviations of their respective means from the total mean. These will sum to zero and represent the gradients between the means of areas centred on points half the map extent apart. Each quarter may itself be divided into four parts and a lower order of gradient obtained in the same way. The procedure is continued down to the individual township level. A discrete and nested hierarchical regional system is formed with a map of values at each scale which are additive so that the original map may be reconstituted by simple addition. If the townships formed a regular lattice, the scale metric would be distance; if all townships were the same size, we could use area. Since neither of these occur for Ontario, we must speak in terms of scale of township aggregation or of hierarchical level although an average distance relationship or a size of areal scale argument is implicit. The procedure is patterned on frequency filtering of a map described by a two-dimensional spectrum but may be interpreted as a trend estimation technique (Curry, 1970). It can be related to statistical systems analysis (Curry and MacDougall, 1971), but we ignore here these mathematical representations. Cascaded averaging and differencing provides a set of maps of increasing scale of generalization which, added together, reproduce the original map. From a historical series of population maps by township, under cascading, each value at each scale is part of a time series which is to be examined for any temporal ordering for use in extrapolation into the future. Separate time series by scale and their combined fore~ casts We went through the cascading procedure for the Ontario population maps and then fitted empirical difference equa-

Forecasting township populations

51

tions to the time series. The forecasts for each of the components into which the township was decomposed were then added to reconstitute the forecast for the township. In general, the results were not good when compared to realized values. There were indeed many close fits, but divergences could be very large without any apparent ordering in the errors to suggest why they were occurring. We can suggest two reasons for the poor results in practice, the first numerical, the second a criticism of the procedure involved. There are only a small number of cross-sections in time, and, if there is sufficient noise in the system, some forecasts are likely to be poor. If each township were being treated in isolation, the prediction error would depend only on how well one time series was fitted by one equation. Where the cascading procedure is used, the error depends on the fit of several regression equations with no reason to believe that individual errors will cancel. This might produce a systematic spatial pattern of errors, but the important objection to the method occurs when township values vary markedly over the map. It is possible for a township of, say, 200 people to have scale components of +50, -850, +1150, -550 and a map mean of +400. Thus, even if the forecast equations are working well individually, prediction errors in absolute terms which can be very large relative to actual township values. While it is possible to divide a map into spatially orthogonal components, there is an important question of the temporal orthogonality of any one of these components. Operationally this is resolved into whether we can form a time series for each of the components, obtain prediction operators for each, and add the results: this is a univariate problem. On the other hand, if orthonormality in time cannot be assumed, then we must deal with the temporal interrelations between the scale components. This becomes a multivariate problem. Referring to our moving average-filtered population maps by townships and decades, no decision can be made a priori. It seems possible, given our poor results, that the large scale/small scale interactions are causing the difference equations for the various levels to be interrelated so that they cannot be fitted and used independently. Regression on lagged scale components Since forecasting each scale component of each township separately and then

52

Urban futures for Central Canada

adding the results from the final forecast gave unreliable results, we handled the separate scale components simultaneously in a multivariate scheme. We have for each township the first and second time differences of each scale component. We can thus write an equation

where An,g is the nth order difference in the period immediately preceeding time t, for the scale component g and an,g is the corresponding weighting coefficient. Given that we have two time differences for each pair of six hierarchical levels, our equation has twelve terms. It is clearly impossible to solve for the as when we can write only eight equations from eleven sets of observations so that we have to reduce the number of explanatory variables. In fact we chose four variables, but, even with this reduced number, we were exceeding our limit in a statistical sense. Although it may well be thought that large and small cities would exhibit differing scale dependencies, no simple relationships appear to exist with respect to city size. If a size argument exists, it must be contained within a spatially complex hierarchical structuring of centres. However any attempts to look for 'causes1 of the way the 'best' equations are distributed in space would clearly be too costly. Our policy has been rather to look not very systematically at the forecasting capability of a range of space and time variables for a small number of townships and pick out sets which performed best over groups of them. A sample of the trial results is presented in table 2.5. No one combination performs better than any other in all cases, but some are obvious non-starters, and we managed to narrow the choice down to five sets of variables. We were concerned to include first- and second-order time differences to maintain the flexibility discussed above; however we were forced to use one equation which did not contain second difference terms. The sets of variables which were used on the full data series to 'predict1 the 1961 and 1971 values were: (1) (2) (3A

TABLE 2.5 Trial forecast schemes:

One-step 1961 forecast error

Gloucester Derby Per cent errorl

Scheme

Four A A^'l consecutive A2'1 mixed AA ' differences ' A ' A increasing A1'3 scale AA ' aggregation A1'4 ,2,4 A 1,5 1

2

2

2

2

3

Four first differences 'A increasing A1'1 scale AA ' aggregation 1,3 1

First and second differences on map average and two other differences 1

2

A1'1 A1'2 A1'3 A1'4 1,4

A2'4 ,1,5 A A2'5 ,1,6 A 2,6

-68 .1 -39 .7 -37 .7 -48 .8 -52 .2 -30 .2 -34 .9 -72 .9 -22 .6

-60 .6 -32 .2 -82 .0 -40 .1 -76 .4 -26 .0 -34 .1 -121 .7 -38 .1

-222.1 69.4 124.6 56.3 15.3 44.9 48.4 258.1 -44.3

A A1'4 ,1,5 A 1,6

-31. 5 -33. 3 -54. 2

-32.0 -28.7 2.0

-19 .9 -12 .5 18 .3

-111.3 -71.6 7.0

169 .0 226 .9 3 .5

-56 .4 -6 .7 -7 .3

21 .1 -11 .7 -12 .5

261.5 72.6 20.3

1.4 -26. 6 -3.7 36. 3 -46. 3

-38.7 -20.6 -95.2 -10.9 -34.4

-17 .1 -27 .6 -43 .6 -73 .1 57 .9

-23.9 -54.9 -76.8 -10.4 -68.1

-42 .7 -60 .0 60 .8 50 .7 51 .6

-128 .3 1.1 -64 .9 -14 .6 -48 .4

11 .7 15 .8 -25 .1 3 .4 -84 .0

232.6 113.5 110.5 99.8 77.7

A

1,4

A1'3 ,1,4 A 1,5

A2'1 A2'2 A2'3 A2'4 1,5

A1'6 A1'6 A1'6 A1'6 1,6

1

4

A1'3

A

3

York

-77 .0 -119 .5 -71 .0 18 .8 -64 .9 -94 .7 -8 .5 199 .0 -50 .9

A

A2'3 AA ' A2'4 ,1,5 A 2,5

1

Ancaster

-0.6 -64.8 -93.7 -87.6 -24.4 -23.5 -51.8 32.4 -35.3

A1'2

2

E Oxford

-20 .3 -47 .7 -22 .9 -19 .0 4.3 -18 .5 -104 .8 15 .3 10 .8

A1'4 ,2,4 A A1'5 ,2,5 A 1,6

2

E Whitby

-26.6 -15.7 -18.4 -38.4 -42.3 -30.9 -33.7 26.9 -64.2

A1'3 ,2,3 A ,1,4 A

AA1'3

Cashel Tudor

8.8 -64. 0 -56. 5 -9. 5 55. 6 35.4 58. 5 -94. 2 -42. 9

*2,2 A

A^'2 A A2'2 AA ' A,2,3

A A^'l

A1'2 AA '

An son Hindon Minden

2 6 A A ' A2,6 A2,6

A2'6 2,6

Per cent error = *"recast-actual actual

54

Urban futures for Central Canada

(4) (5) Detailed procedures In cascading a map the deviations will always equal the township value; with change variables this is also the case. However, when we go into the regression procedure, using first and second temporal differences for some only of the hierarchical areas, and insert coefficients, it is unlikely that the intersect values will be zero. They are usually small, but can be large. However we have neglected them because, once the regression procedure is used for pushing into the future, involving the cascading of future maps, the deviations obtained will be different from those in the past and consequently the intersect value will become more and more irrelevant. When one is forced to fit coefficients up to the limit of the degrees of freedom given by the small amount of data, one is almost in the position of solving deterministic equations. Thus virtually all of the variance is explained by just about any combination of areal variables, but this normally desirable result has absolutely no relation to how well the equation forecasts. One has literally no idea whether the forecast will be right on target at 100,000, be up in the 300,000s or give -200,000. It might seem possible to try all permutations for a township and pick out the equation which performed best on the trial year, repeating for each township. However computer costs would be prohibitive. It is in fact not an easy problem to decide which of the equations is 'best,' even with forecasting values which can be checked with known values. Even with the same equation, a one-step prediction from 1951 to 1961 may have considerable error, while a comparable prediction from 1961 to 1971 may be close. The two-step prediction from 1951 to 1971 may have a different margin of error yet again. Finally the 1981 prediction which can only be checked as to its general reasonableness, can provide still a different criterion. For all townships having populations over 19,000 in 1961 - these are the main urban areas of Ontario - our main criterion was the reasonableness of the 1981 forecast. For townships having smaller populations, where it is difficult to decide on reasonableness (and for the above-mentioned towns in the few cases of doubt), the one-step 1971 prediction was weighted as most important, while the 1961 forecast was weighted least, because of the 'abnormal1 growth from 1951

Forecasting township populations

55

to 1961. Even with this choice of 'best' equations, it should not be forgotten that our criteria refer only to the local township values. It is not impossible that the 'best1 equation locally will produce a set of values which, because they affect the values of other townships through the regression equations, might not be 'best1 in terms of these related areas. Indeed the choice of a different equation in one area should involve a new search for 'best1 equations elsewhere. However such a quest could go on indefinitely and was not undertaken. One feature which did emerge as the spatial distribution of forecast equations was being examined was a local ordering in the way that the equations performed. Townships to which a given equation applied grouped by districts. Moreover it was usually the case that the equations on either sides of a boundary performed almost as well for a township near the boundary. In general the equation which performed best was chosen, except that occasionally the next best equation was chosen if the equation performing best was not represented in the neighbourhood of the township in question. The rationale was that the 'second best' was mirroring the change best in the neighbouring area and consequently was likely to do so for the deviating township also. Generally we hoped that confidence gained from spatial homogeneity could be transferred to regularity in temporal ordering and thus to the reliability of the scheme in future years. When we were checking the results of test years, there was little spatial pattern in the deviations from the correct values. In the Toronto area there was a complementing of positive and negative errors, so that the overall value was near the mark but otherwise the appearance was next to random. The frequency distribution of these values is adequately described by a normal density function which stresses the point that we cannot expect all our forecasts to be equally good. We might hope to concentrate the distribution of errors more closely around zero, but, since we expect that errors are being generated as a normal process, about a third of the values must be over one standard deviation from zero. The method in operation The forecast procedure we have used is quite simple in its outline, but extremely complex and dynamic in its operation.

56

Urban futures for Central Canada

It seems worth discussing the way in which it generates a series of forecasts, for we frequently find results that at first seem surprising, but can be explained by reference to the dynamics of the evolving spatial pattern. We first of all perform cascaded averaging and differencing on a series of maps to generate a time series of deviations for each scale level. This tells us how well each area is competing for growth increments at that scale. We now split each time series of deviations into two by taking first and second time differences. The first differences tell us how much the deviations about the hierarchical means are changing; the second differences tell us the rate at which these changes are taking place. For every township we now have a matrix of information to use as the basis for our forecasting, and a new vector of information each time we cascade a forecast map. This vector provides us with a spatial feedback mechanism to guide our forecasting scheme. We now have to decide, for each area, at what scales the most important information lies and fit regression coefficients to some of the sets of space-time differences. A relationship exists between the regression coefficients and the differences that determine whether growth is a p61arizing, competitive process or whether it diffuses to the mutual advantage of neighbouring townships. The time-space values provide the variable inputs to the forecast equations, but the shape of the regression operator determines what effects they will have in any one area. We can illustrate the process with one or two examples. The township of East Whitby, to which Oshawa's population has been added, is an interesting one. The time-space series used for the forecast are first differences for the two highest levels of the cascade, and both first and second differences for the map mean. Thus the more important determinants of Oshawa's growth seem to stem from the competitive ability of the larger regions of which it is a part. Recall that the actual forecast is generated by the following equation:

In particular, for this township we have

Forecasting township populations

57

If the signs of the regression coefficient and of the time-space value (A^j) agree, then their product is positive and the forecast receives a 'growth' impulse. Conversely opposite signs induce 'declines.' This has an interesting interpretation. It tells us whether the township gains or loses by increase rates that are similar to its neighbours at that scale. Where growth is highly competitive, the advantage lies in increasing faster than one's neighbours. Oshawa, however, provides us with an example of complementary growth. The 1981 forecast is for 174,000 people, a 39 per cent increase over 1961, but the 1991 forecast is for 198,000, only a 14 per cent increase. Why did this rate fall off? Remember that the 1981 forecast is based on 1961-71 timespace changes and the 1971 population figure. Substituting the required values (table 2.6) into the forecast equation, we have,

From the regression coefficients the major determinants of Oshawa's growth are therefore the first differences for this quadrant of the map and the first difference for the map average, (A^ 5; Aj_ 5). Growth occurs if this map quadrant's growth does not greatly outstrip that of the other three and if the study area as a whole experiences strong growth. The corresponding substitution for the 1991 forecast is,

We can see that the quadrant's relative increase has declined (2165 to 1097), but so too has the increase in the map mean (2802 to 1575), and this more than offsets the advantage. Thus Oshawa grows more slowly between 1981 and 1991 because Ontario grows slowly from 1971 to 1981, even though the regional allocation of the increments was more even. As in most of the highly interconnected urban areas of the 'golden horseshoe,' Oshawa's development moves hand in hand with its neighbours. However this pattern of development in the forecasts is by no means unique. Towards the north of the study area, in Muskoka county, growth is polarized and only the strongest centres seem to survive (figure 2.1). Gravenhurst (Muskoka township) is one of the

58 Urban futures for Central Canada TABLE 2.6

1891-2001 time-space differences for E Whitby Township (Oshawa)

Most recent year of data utilized 1891 1901 1911 1921 1931 1941 1951 1961 1971 1981 1991 2000 Regression coefficients

Population in OOOs

43 65 126 174 198 232

Time-space differences A

A

A

1052 64 1934 2087 2159 843 2584 7285 8504 3658 4028

-5 -97 405 582 665 339 964 1919 2165 1097 1429

288 46 476 681 788 589 1459 2983 2802 1575 1949

-368 -242 430 205 107 -199 870 1523 -181 -1226 374

1.394

-18.445

27.547

3.399

l,4

l,5

l,6

A

2,6

areas that grows even though its forecasts depend upon precisely the same sets of deviations as Monck and Morrison townships immediately to the north and west, areas that are suffering declines. For an explanation we must look to the structure of the regression operators. Gravenhurst's 1981 population is given by

The corresponding equations for Monck and Morrison townships respectively are

The 1981 forecasts for Monck and Morrison townships use the same space-time series (Aj[ js) f but the regression co-

Forecasting township populations

59

efficients on the map average (33 and 34) are considerably lower, and it is these coefficients that determine the area's response to the 'signal1 from the rest of the map. Here the larger towns such as Gravenhurst or Bracebridge have a much greater ability to benefit from the growth of Ontario than the smaller areas that surround them, overwhelmed as they are by their location in an area of generally slow growth. Other patterns of behaviour are also evident in the forecasts. It is common for small townships in the south to be responsive to changes in neighbouring cities. The pattern for Dumfries South is positively related to the ability of the local area to maintain relatively high increase rates, and its decline over the last ten years of the forecast period may be traced to the failure of neighbouring Brantford to maintain the rate of increase in its growth through the previous decade. REFERENCES Box, G.E.P., and Jenkins, G.M. 1970. Time Series Analysis, Forecasting and Control. San Francisco: Holden Day Cliff, A.D., and Ord, K. 1971. 'A Regression Approach to Univariate Spatial Forecasting,' in M. Chisholm, A.E. Frey, and P. Haggett, eds, Regional Forecasting. London: Butterworth Curry, L. 1970. 'Univariate Spatial Forecasting,' Proceedings IGU Commission on Quantitative Methods, Economic Geography, 46/2 (supplement): 241-58 Curry, L. 1971. 'Applicability of Space-Time Moving-Average Forecasting,' in M. Chisholm, A.E. Frey, and P. Haggett, eds, Regional Forecasting. London: Butterworth Curry, L., and MacDougall, E.B. 1971. Statistical Spatial Analysis and Remotely Sensed Imagery, unpublished monograph Jenkins, G.M., and Watts, D.G. 1968. Spectral Analysis and Its Applications. San Francisco: Holden-Day Miller, R.G. 1967. 'Advanced Topics of Statistical Prediction in Meterology,' Statistical Analysis and Prognosis in Meterology, Technical Note 71. Geneva: WMO. Pp 11533

60

Urban futures for Central Canada

3 Forecasting urban populations JAYSIEGEL One would suspect that forecasting the future population of an urban area would be a straightforward proposition. The federal government in Canada conducts a detailed census of population every ten years and summary censuses every five years. In addition, there are extensive life tables tested and used by insurance companies, which provide the necessary historical and biological information to generate estimates of the stream of future populations. This paper provides a framework for interpreting the population forecasts for cities in Central Canada (those cities presented in appendix B). In order to achieve this objective it is necessary to discuss first the methodology and techniques of forecasting in general. Such techniques are not restricted to populations and can be used to forecast other aspects of the urban environment such as land use, employment, and density of interaction. However in planning for the future requirements of an urban area, forecasted population is usually one of the first and most important components to be obtained. To be sure there are problems of defining the urban area (as discussed in the first paper); however the most difficult problem arises from the simple fact that human populations are unique in that they can control the variables that determine their future numbers. Birth and death rates can be modified by altering the resources devoted to public health, education, and contraception. The 'baby boom1 after World War II is a dramatic example of the social nature and variability of these biological variables. During the thirties demographers were concerned with the declining growth rates of the western nations and about the effects of a stationary population on economic growth. However after the war the population forecasts proved to be totally inaccurate, and the resulting rapid growth put severe pressure on many social services and institutions, particularly schools.1 The major source of difficulty in forecasting the future population for urban areas is migration. This variable is exceedingly important in determining forecasts for urban

Forecasting urban populations

61

areas and becomes more variable as smaller areas are considered. As we shall see below, the effect of this variability may be to swamp entirely the biological components of population growth. Interurban migration is particularly sensitive to the relative economic condition of urban areas in Canada. It is not unreasonable to combine stable population growth at the national level with large disparities in growth rates at a regional or urban level. METHODOLOGY OF FORECASTING Any forecast of the future population of an urban area is obtained by one of three methods: (1) by determining the optimum level; (2) by the direct method; or (3) by the indirect method. The first method recognizes the ecological aspect of population growth and attempts to utilize a model to determine the optimum level of population for an urban area. As with most ecological issues, this method is likely to incorporate policy questions along with the forecasts. Lithwick (1970), for example, has advocated such an approach. However to date this approach has been of only theoretical interest and has not generated specific forecasts.2 The second method, the direct one, assumes that the future population can be forecasted directly from the demographic variables describing the present population and growth trends in the recent past. The indirect method, on the other hand, bases the forecast on other (non-demographic) socioeconomic variables or indices which describe the urban system. The latter two methods differ in their assumptions of what is the generating mechanism of urban growth. The direct method assumes that people themselves, through the demographic structure, are the generators of growth, and therefore this method uses a supply approach to growth in the urban economy. The indirect method, however, argues that people will respond to economic situations largely through migration, on the assumption that the socioeconomic condition of the urban economy is the driving force behind population growth. This clearly is a demand approach to urban growth. The basic weakness of both the direct and indirect methods of forecasting lies in the variables or relationships which are assumed fixed or constant over the forecasting period. If an urban area passes through phases or stages in the growth process in which the form of the underlying relationships change, often quite sharply, the forecaster is presented

62

Urban futures for Central Canada

with an almost insurmountable problem. In Boulding's analogy 1 ... who would forecast the brilliant butterfly from the study of a caterpillar?1 However, this 'phase-shift1 limitation can be recognized and to some extent accommodated. One of the most common means is the presentation of a group of forecasts resulting in a band instead of a single series of predictions. By far the majority of forecasts are obtained by the direct method. In fact, all of the forecasts in appendix B except one are obtained directly. The one exception is the forecast of the Ministry of State for Urban Affairs, which is based on the projection of urban employment demands in the different census metropolitan areas (CMAs). Isard (1960) has developed a classification of the different direct forecasting techniques. This classification scheme is presented in table 3.1 and will be useful in organizing the forecasts presented in appendix B. We look at each of the major types in turn. TABLE 3.1 Direct forecasting techniques:

A summary

A COMPARATIVE FORECASTING B PROJECTION BY EXTRAPOLATION 1 Graphic techniques 2 Extrapolation by mathematical function a. polynomial curves b. exponential curves c. gompertz and logistic curves C RATIO AND CORRELATION METHODS 1 Ratio methods a. ratio to total population b. ratio to population components 2 Regression and covariance analysis D GROWTH COMPOSITION ANALYSIS 1 Natural-increase methods a. crude birth and death rates b. cohort-survival 2 Inflow-outflow analysis a. natural increase adjusted for migrants

Forecasting urban populations

63

Comparative forecasting This method is relatively simple. The procedure identifies a mature area that has already completed its growth process. The forecast for the study area is obtained by extending its growth curve into the future following the pattern of the past experience of the 'mature1 urban area. The problems with this method are obvious: (1) the subjective nature of choosing the mature urban area; (2) the difficulty of assuring that the two areas are 'identical1; and (3) the assumption of no major structural change. Perhaps the most appropriate use of this method is in forecasting the growth of new towns. One might be able to apply past experience on the timing of new towns to generate a forecast for the growth of another new town during the initial development process. Projection by extrapolation This method, probably the most common, assumes that the future is contained completely in the area's past growth experience. Furthermore it assumes that the growth process will be smooth and regular. Under these assumptions this procedure uses past population changes and extrapolates these into the future. The extrapolations can be graphical, first fitting a curve to the past and extending it forward in time, or mathematical, estimating the parameters of the model from past experience and simulating future growth to achieve the forecast (see Curry and Bannister, paper 2). This process entails many technical decisions. In graphical extrapolations one must decide on linear coordinates, double or semi-log plots, and so forth. With mathematical extrapolation one must decide on the appropriate form and complexity of the model. The biggest drawback of the extrapolation approach is the assumption of stability. Extrapolations assume that there will be no shift in exogenous factors. This assumption becomes more tenuous the longer the forecast period, as changes in government policy or phase shifts in the stage of growth or maturity of the urban area increase the unreliability of the forecast. Ratio and correlation methods Population growth of an urban area may bear a relationship to the growth of another area, especially if there are strong interconnections among factors determining growth in the two areas. The ratio method is similar to the comparative method of forecasting, but improves on that method in

64

Urban futures for Central Canada

several ways. First, it does not assume that the future of one urban area will repeat the past of another, and second, it forces one to identify explicitly the relationships Connecting1 the two areas. In its simplest form the ratio method uses a constant ratio to project into the future. However this method can be modified by allowing for the ratio to vary in order to account for a shift in the position of the urban area (e.g., a shift from reliance on the industrial sector to the service sector). There are two basic ways in which the ratio method can be applied and they differ with respect to the reference base or denominator. The basic reference value can be either an aggregate (or total population) or a component of the population of the study area or reference area. An example of the first would be using the ratio of Toronto's population to the total Canadian population: given this ratio, and a forecast of the population of Canada, it is then possible to obtain a forecast for the future population of Toronto (see Miron, paper 4). Criticisms of this method for obtaining a forecast for the future populations of an urban area are similar to those for the extrapolation method. The ratio method represents a simple hypothesis concerning the relationships between the growth of populations in the study area and the reference area. This simple hypothesis can be extended through the use of more sophisticated statistical hypotheses utilizing regression and correlation methods. With these techniques population growth in the study area is associated statistically with other factors such as income, employment, investment, exports, school enrollment, rents, telephone installations, automobile registrations, and the like. This method differs from the indirect method in that no specific direction of causality or model of growth is assumed. The goal of the regression or covariance method is to reduce the 'unexplained1 variation of the population growth in the study area. The validity of this approach as a means of forecasting depends crucially on the assumption that the true causal relationship existing in the past will be the same in the future. We may very well have a situation where the variation in population, the dependent variable, is statistically related to the variation in an independent variable when in reality both variables are causally related to a third unidentified variable. In addition, there are problems with the usual statistical assumptions: normality, independence, and constant variance.

Forecasting urban populations

65

Growth composition analysis This method relies on the demographic components of population growth for the urban area. Given rates of natural increase or decrease and of net migration, and political boundary changes of the urban area, it is possible to construct a forecast of the future population. The accuracy of such a procedure depends on the validity and stability of the vital statistics. One of the most precise techniques is the 1 cohort-survival' method, which disaggregates the population by age and sex. The number of survivors from each group at the end of a given point in time can be determined from agespecific mortality tables. This group is then transferred to the next largest group. Natural increase is obtained through net migration and birth, both estimated from agespecific rates. This process is repeated, and the forecast is obtained for each period, usually five years. This procedure is as accurate as the mortality and birth rates used, but for urban areas the more serious problem is the migration component. Only when the difference between in- and out-migration is negligible will this procedure give an accurate forecast. Unfortunately, for large urban areas in Canada migration has been a very significant and unstable component of historical population growth (see Stone, 1967, table 5.5). SUMMARY OF FORECASTS On the basis of this brief review we can now turn to the discussion of specific forecasts. Appendix B presents an extensive compendium of population forecasts for cities in Central Canada. These series forecast the population of those Ontario cities and Quebec cities which were defined as metropolitan or major urban areas in the 1966 Census. Forecasts were prepared for smaller centres - over 10,000 population but are not included here. At the time of the 1966 Census there were 9 metropolitan areas (CMAs), 7 in Ontario and 2 in Quebec, and 23 smaller major urban areas (MUAs), 14 in Ontario and 9 in Quebec.3 The forecasts were obtained from a variety of published documents: planning reports, government studies, consultants submissions, as well as from analyses undertaken within the Urban Environment Study project described earlier. As-such they represent different images of the future and varying methods of approach. As background for subsequent sections

66

Urban futures for Central Canada

in this volume, the rest of this paper summarizes for these centres the maximum, minimum, and median projections (at the end of the projection period) from the list in appendix B. The forecasts vary in accuracy and in detail of coverage as well as in purpose. The major population forecasts project to the year 2000 in five-year intervals. The minor forecasts project over a shorter period; in some instances the projection is for only a single target year. The following discussion is concerned only with the major long-term population forecasts. The minor forecasts were usually contracted for each city individually with a specific goal in mind and are difficult, if not impossible, to compare across cities. All but two of the major forecasts are based on growth compositional analysis of the population (technique group D in table 3.1). They make similar assumptions in constructing the age-specific cohort-survival tables, but draw on different assumptions concerning migration. The Ministry of State for Urban Affairs (Lithwick, 1970) projections, for example, used the indirect method, and the Centre for Urban and Community Studies (CUCS) projections, deriving from the Urban Environment Study, were constructed using a simple logistic extrapolation of past population growth (technique B-2-c in table 3.1) . Tables 3.2, 3.3 and 3.4 give a capsule presentation of the major forecasts presented in appendix B. Three series are presented for each CMA: the upper and lower bound and the median forecast. For the smaller-size categories of major urban agglomerations and other centres only the median forecasts are included. In analyzing the series in these tables one must first determine the spatial definition of each city and the assumption, explicit or implicit, as to how this definition will vary over the forecast horizon. These boundary difficulties can be quite significant. What will Montreal, Toronto, Oshawa, or Guelph, for example, encompass in 1981 or 2001? Most of the urban forecasts are vague on this point, and it must therefore be assumed that the city is considered to be physically 'boundless,' with past boundaries irrelevant and with future boundaries expanding in direct proportion to population. The effect of boundary changes at different points in time is clearly apparent in the following example of Metropolitan Toronto (table 3.5; see also paper 1). In practice changes in definition tend to occur in large increments, each census using a different set of criteria for areal delimitation (see the discussion in Stone, 1967).

TABLE 3.2 Projected populations for metropolitan areas (CMAs) in Central Canada at five-year intervals from 1961-2001 (in OOOs) Urban area

Series

1961 1966

1971

1976

1981

1986

1991

1996

Hamilton

High Median Low Actual

521 499 483 496

613 557 522

734 627 570

881 698 625

1046 771 677

1229 860 724

1444 915 774

cues

395

449 449 449 449

236 215 209 224

293 246 229

369 283 252

463 321 277

574 360 304

710 406 331

882 436 361

cues

155

192 192 192 192

242 230 223 284

287 257 240

344 289 261

413 322 285

490 355 307

597 396 328

685 422 352

cues

181

207 207 207 207

586 562 428 596

700 634 471

845 711 518

1019 793 568

1215 876 618

1432 955 666

1684 1031 714

430

495 495 484 495

142 134 115 154

176 148 113

222 166 112

281 183 110

349 202 108

427 224 104

522 238 100

111

121 117 117 117

2158 2158 2100 2158

2666 2531 2200 2610

3337 2926 2303

4239 2983 2442

5412 3810 2599

6850 4276 2750

8592 4736 2885

10754 5185 3016

Kitchener

London

High Median Low Actual High Median Low Actual

Ottawa

High Median Low Actual

Sudbury

High Median Low Actual

Toronto

High Median Low Actual

1824

2001

Source

IQASEP

IQASEP DBS IQASEP IQASEP DBS IQASEP IQASEP DBS IQASEP SRG ODTE DBS IQASEP

cues

IQASEP DBS IQASEP SRG MTPB DBS

Table 3.2 continued

Urban area

Series

Windsor

High Median Low Actual

Montreal

High Median Low Actual

Quebec

High Median Low Actual

1961

1966

1971

1976

1981

1986

1991

1996

232 229 210 2551

258 247 207

289 266 208

324 287 203

360 307 200

397 326 196

193

212 212 212 212

438 344 191

2821 2739 2671 2725

3340 3097 2911

3977 3529 3180

4755 4020 3517

5675 4530 3919

6739 5055 4410

2110

2437 2437 2437 2437

7945 5639 5016

LITHWICK IQASEP LITHWICK DBS

473 466 439 476

545 523 466

631 581 495

735 643 524

858 705 551

358

413 413 413 413

1001 767 574

1170 828 595

LITHWICK BSQ IQASEP DBS

2001

Source

IQASEP SRG IQASEP DBS

CODES FOR SOURCES OF PROJECTIONS (see appendix B) BSQ Bureau de la Statistique du Quebec IQASEP Institute for the Quantitative Analysis of Social and Economic Policy, University of Toronto CUCS Centre for Urban and Community Studies, University of Toronto SRG Systems Research Group ODTE Ontario Department of Treasury and Economics MTPB Metropolitan Toronto Planning Board LITHWICK Urban Canada Problems and Prospects, Ministry of State for Urban Affairs , Ottawa 1 Greater than 10 per cent increase in population due to redefinition of boundaries

TABLE 3.3 Median projected population for major urban areas (MUAs) in Central Canada at five-year intervals from 1961-2001 (in OOOs)

Urban area ONTARIO Brampton Brantford Cornwall Guelph Kingston Niagara Falls Oshawa-Whitby Peterborough St Catharines Sarnia Sault Ste Marie Thunder Bay Timmins Welland QUEBEC Chicoutimi Drummondville Granby St Jean St Jerome Shawinigan Sherbrooke Trois Rivieres Valleyfield

1961 actual

1966 actual

1971

1976

1981

1986

1991

1996

2001

Source

60 67 45 57 79 68 124 60 123 75 84 108 43 66

76 72 53 62 87 75 146 65 137 82 93 118 46 74

85 78 58 68 95 84 177 69 153 92 103 130 49 82

116 83 62 75 103 92 207 74 170 101 114 142 53 90

138 89 65 81 111 101 239 79 187 110 125 154 56 99

160 95 68 87 119 109 272 84 203 119 135 166 60 107

183 99 73 93 127 118 272 88 220 128 145 178 63 116

ODTE ODTE

24 42 63 55 81 50 96 61 58 93 40 36

45 62 40 51 72 61 100 56 109 67 75 98 40 59

ODTE ODTE ODTE ODTE ODTE ODTE ODTE ODTE ODTE ODTE ODTE

105 39 30 35 25 64 70 84 30

116 41 34 39 27 67 80 104 37

118 44 43 42 42 65 89 109 38

119 48 48 44 47 63 99 114 39

121 51 53 47 53 62 109 119 41

123 55 58 50 59 60 120 124 43

123 58 63 52 65 57 130 128 44

121 61 68 54 72 54 141 131 45

118 64 73 56 78 50 152 133 45

BSQ BSQ BSQ BSQ BSQ BSQ BSQ BSQ BSQ

18 572 o

cues

1971 actual1

(Toronto) 80 49 63 86

T

3013 120 64

(Niagara) 78 81 112 41

(Niagara) 1323 47 34 47 27 57 85 98 37

Table 3.3 continued

CODES FOR SOURCES OF PROJECTIONS (see appendix B) BSQ Bureau de la Statistique du Quebec IQASEP Institute for the Quantitative Analysis of Social and Economic Policy, University of Toronto CUCS Centre for Urban and Community Studies, University of Toronto SRG Systems Research Group ODTE Ontario Department of Treasury and Economics MTPB Metropolitan Toronto Planning Board LITHWICK Urban Canada Problems and Prospects, Ministry of State for Urban Affairs, Ottawa CHSS Canadian Highway Systems Study 1 Preliminary 1971 Census figures. Names of centres in parentheses represent incorporations of centres into expanded 1971 census boundaries. 2 Projections inflated due to recent annexation (see table 3.5) 3 Greater than 10 per cent increase in population due to redefinition of boundaries in creating a new metropolitan area TABLE 3.4 Median projected population for other urban centres, Central Canada 1966-2001 (in OOOs)

ONTARIO Barrie Belleville Brockville Chatham Cobourg Georgetown Kenora Lindsay

1966 actual

1971

1976

1981

1986

1991

1996

2001

Source

1971 actual

24 33 19 32 12 12 11 12

29 36 22 37 13 16 12 13

33 39 24 42 14 22 13 14

39 43 27 48 16 28 14 15

44 46 30 54 17 34 15 16

50 50 33 60 19 39 16 16

57 53 37 66 21 45 17 18

61 57 39 72 23 49 17 18

CUCS ODTE CUCS ODTE CUCS CUCS CUCS CUCS

28 35 20 35 11 17 11 13

Table 3.4 continued 1966 actual

1971

1976

1981

1986

1991

1996

2001

Source

North Bay Orillia Owen Sound Pembroke St Thomas Stratford Trenton Woodstock

24 21 18 16 23 23 14 24

42 23 18 18 25 25 15 26

43 28 18 19 26 25 16 29

45 32 19 20 28 27 18 32

50 na 19 21 30 na 19 35

54 39 20 23 32 30 21 39

58 na 21 25 35 na 23 43

63 na 21 25 37 na 24 46

cues

QUEBEC Alma Asbestos Joliette La Tuque Magog Rouyn-Noranda Rimouski Riviere du loup St Hyacinthe Sept Isles Sorel Thetford Mines Val d 1 Or Victoriaville

22 11 19 14 14 32 20 12 24 19 19 22 12 21

26 11 36 15 14 32 30 13 24 25 19 26 17 24

27 11 40 16 15 32 32 14 25 29 20 25 19 26

29 12 44 18 15 31 35 15 27 34 22 25 21 30

31 na 48 20 16 31 37 16 29 41 23 24 na 33

33 14 52 21 17 30 40 17 30 47 25 23 24 37

34 na 57 23 17 30 42 18 32 55 27 22 na 41

35 na 61 25 18 29 44 19 33 62 28 21 na 44

For source codes see table 3.3; na = projection not available. 1

Major boundary change

CHSS

cues cues cues CHSS

cues cues BSQ CHSS BSQ

cues cues

BSQ BSQ

cues cues BSQ

cues BSQ CHSS

cues

1971 actual 491 24 18 17 (London) 25 15 26 23 10 351 13 13 31 27 13 25 24 19 22 17 22

72

Urban futures for Central Canada

TABLE 3.5 Boundary changes and the population of the Toronto urban area

Year

Census definition

1941 1951 1961 1971

City MA CMA CMA

1

.

667,000 1,118,000 1,824,000 2,628,000

Population of fixed area (1961 CMA) 964,000 1,210,000 1,824,000 2,465,000

Each metropolitan area unit (1951, 1961, 1971) used different criteria in its construction.

The crucial question in any forecast is whether the definitial criterion remain constant? The Curry-Bannister township-based forecasts in appendix A are easily evaluated in that they permit the reader to aggregate townships into any lattice of larger spatial units. But what of the city-specific forecasts in appendix B? For the most part they appear to be based on the definition of urban or metropolitan areas used in the 1961 or 1966 Censuses. Our own (CUCS) forecasts were based on these units. Since some spatial growth is due to outward migration or spread of population from within the 1961 spatial area, this 'fixed1 area definition could well show a declining rate of growth over time. There are, in addition, numerous other problems. The 1971 Census, because of the introduction of a new definitional concept, the labour supply area, probably overestimates the existing population for most urban or metropolitan areas. Furthermore many urban regions defined in 1961 will be aggregated or absorbed with nearby places by the census in the year 2001. Should the forecasts for Metropolitan Toronto, for instance, be interpreted as an expression of Toronto as a single, physical aggregate, or as a loosely structured urban field including the estimated future populations of Oshawa, Barrie, or other outlying and presently separate urban areas? The answer is both; but it is not a very satisfactory answer.4 Comparison of forecasts Table 3.2, presenting the summary range of population forecasts for CMAs, reveals a consistent pattern of growth variability within the urban system of Central Canada.

Forecasting urban populations

73

Research by the Institute for the Quantitative Analysis of Social and Economic Policy (IQASEP) provides the upper and lower bounds of most of the forecasts, with only three important exceptions: Montreal, Toronto, and Quebec City. The median series for the majority of cities is the one generated by the Centre for Urban and Community Studies (CUCS), which is to be expected, given that these projections are in themselves averages of trends over past decades. The IQASEP projections use an age-specific cohort-survival method with varying assumptions about fertility and net migration (technique D-2-a in table 3.1). This procedure is not unique to the IQASEP forecasts, as other series in appendix B also generate forecasts based on both high and low fertility rates. What is unique is how the IQASEP projections incorporate migrants. They include the interaction between migration and natural increase within the five-year period to which the migration refers, by including an approximation formula for the contribution of migrants to total births. In addition, net migration is on a percentage basis instead of an absolute level as in many of the other series. The IQASEP method is more realistic in its treatment of the migration component and its direct effect on population growth. The results in table 3.2 stress again how important migration assumptions can be to forecasting an urban system. When the IQASEP study assumed high migration, it produced the upper bound of the series; when it assumed low migration, it produced the lower bound. The exception in the case of Toronto is the result of the Metropolitan Toronto Planning Board's (MTPB) very strong assumption of zero net migration to Toronto. The township forecasts in paper 2 are constructed from an entirely different procedure than the CMA-city forecasts and therefore can provide a cross-check for the forecasts presented in appendix B and summarized in tables 3.2, 3.3, and 3.4. Table 3.6 presents the Curry-Bannister township forecasts aggregated into the appropriate areas for major cities in southern Central Ontario. The aggregations correspond as closely as possible to the 1961 spatial definitions of metropolitan and major urban areas. The results for Hamilton, Niagara-St Catharines, and Windsor are surprisingly similar to the median forecasts in tables 3.2 and 3.3 (Niagara and St Catharines combined). The township forecasts generate a 2001 total population of 1,599,000 for these three urban areas, whereas the median predicts 1,597,000, a negligible

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Urban futures for Central Canada

TABLE 3.6 Forecasts for census urban areas and cities in Southern Ontario constructed from township population projections (population in OOOs)

Urban area

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Barrie Belleville Brantford Chatham Cornwall Gait Guelph Hamilton Kingston Kitchener London Niagara-St Catharines Oshawa Ottawa

15 16 17 18 19 20

Peterborough Sarnia Stratford Toronto Windsor Woodstock

1961 Census designation 1971 city city MUA city city city city CMA MUA CMA CMA MUA (combined) MUA CMA (Ontario) city MUA city CMA CMA city

Forecasts 1981 1991

Iestimated Ipercentage jIncrease, 2001 ]L971-2001

31 40 83 52 51 43 61 490 85 224 234

32 41 92 56 58 43 73 627 92 254 269

32 40 97 61 58 57 82 782 106 298 296

34 46 100 67 56 57 94 919 135 346 319

9 14 21 29 9 31 54 87 59 55 36

207 151

215 206

234 239

320 291

54 93

474 522 401 592 58 70 82 84 78 86 110 76 33 26 33 32 2,377 2,686 3,071 3,676 222 272 316 360 28 43 33 36

48 43 41 21 55 62 55

difference. For the remaining three CMAs in southern Ontario, Kitchener, London, and Toronto, the Curry-Bannister forecasts are similar to the lower bound forecasts. The aggregated forecasts for cities in table 3.6 can also be compared with the forecasts for smaller cities in Ontario constructed by the Ontario Department of Treasury and Economics (ODTE) and the CUCS. The combined 2001 population for the cities of Brantford, Guelph, Kingston, Oshawa, Peterborough, and Sarnia is 807,000 in the ODTE forecasts, 814,000 in the township forecasting scheme, 850,000 in the CUCS series, all within 5 per cent of each other. There is some variation in individual forecasts, but it is well within reasonable bounds. As with the CMA comparisons, these are similar to the lower bound forecasts and give additional

Forecasting urban populations

75

weight to the validity of the range of forecasts presented in the appendix. However, given the different methods of aggregating spatial units, some major departures between the forecasts in tables 3.2, 3.3 and 3.4 and those in table 3.6 are to be expected. Toronto, as previously noted, is considerably underbounded in the analysis based on township data; the result is an extremely low population projection at the end of the century relative to most other studies. Other centres such as Barrie are also underestimated. The use of the census definition 'city' in such cases clearly ignores the small but growing suburban development taking place in the adjacent townships. In the case of Barrie this includes considerable overspill population from Metropolitan Toronto. Even the new definitional unit employed in the 1971 Census, the urban agglomeration, is unable to capture the extent of expansion in such centres. Table 3.7 presents the intercensal percentage population increase for the CMAs in table 3.2. For all but three CMAs there is a regular pattern. The high growth series has a percentage increase on the order of 45-50 per cent, the median series is on the order of 25-35 per cent, and the low series around or below 20 per cent. Within each series there is little fluctuation over time.5 The three exceptions are Sudbury, Windsor, and Toronto. The first two have some unique properties: Sudbury is dominated by one industrial activity and Windsor is dominated by the neighbouring Detroit metropolitan area. Toronto, on the other hand, presents a major problem which needs further explanation. The high growth series, based on high fertility and high migration, predicts a population of 11 million; whereas the low growth series, based on zero migration, predicts 3 million, less than half a million greater than the 1971 population. This demonstrates once again how important the migration assumption is and how disparate the resulting forecasts can be over a long-term horizon. In addition, Toronto is the only CMA to have an unstable series. The median forecast predicts an intercensal increase of 17.8 per cent for 1971-81, followed by a 43.3 per cent surge between 1981-91, tapering off to less than half this rate, 21.2 per cent for the 1991-2001 period. Intuitively such fluctuations seem unlikely, and this series therefore must be suspect. Clearly Toronto constitutes the crux of the forecasting problem for Ontario, as Montreal

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Urban futures for Central Canada

TABLE 3.7 Intercensal population increase for selected CMAs in Central Canada (per cent) CMA

Series

Hamilton

High Median

Kitchener

High Median

Low

Low

London

High Median Low

Ottawa

High Median Low

Sudbury

High Median Low

Toronto

High Median Low

Windsor

High Median Low

Montreal

High Median Low

Quebec

High Median Low

1971-81

1981-91

1991-2001

40.9 25.6 18.0

42.5 23.0 18.8

38.0 18.7 14.3

56.4 31.6 20.6

55.6 27.2 20.6

53.6 21.1 18.8

42.2 25.6 17.4

42.4 22.8 17.6

39.8 18.9 14.6

44.2 26.5 21.0

43.8 23.2 19.3

38.6 17.7 15.5

56.3 23.9 -2.6

57.2 21.7 -3.6

49.6 17.8 -7.4

59.0 17.8 11.0

61.6 43.3 12.6

57.0 21.2

24.6 16.2 -1.0

24.6 15.4 -3.8

21.7 12.1 -4.5

41.0 28.8 19.1

42.7 28.4 23.2

40.0 24.5 28.0

33.4 24.7 12.8

36.0 21.3 11.3

36.4 17.4

9.7

8.0

does for Quebec, not only because each contains a high proportion of the population to be predicted and therefore has a profound influence on growth throughout the whole urban system, but also because so much of the growth of each is exogenously determined and consequently difficult to predict. It is reasonable to conclude from the above comparisons that the forecasts summarized in tables 3.2, 3.3, and 3.4 are relatively consistent and do circumscribe a reasonable expectation for possible future populations for cities in

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77

Central Canada over the next 30 years. Structural transformations in Central Canada Canada has undergone several fundamental changes in its social and economic structure in the first decades of the twentieth century. There is every reason to believe that this process of structural change will continue, perhaps at an accelerated rate. The last quarter or third of this century may even bring cataclysmic changes - such as energy - in the post-industrial society. Ideally these structural changes should be incorporated directly into the methodology of the population forecasts, but this is an extremely difficult proposition and beyond the current state of the forecasting art. However it is possible to give some idea of how these changes will affect the efficacy of the population forecasts presented here. Many of the specific issues involved are discussed later, in the papers in parts II and III. It is possible to identify at least three major areas of structural transformation in Canada: 1 2 3

evolution toward an almost totally urban or metropolitan society; a shift within the economic structure to the service sector and the professions; obsolescence of many areas, both urban and rural.

These three areas of change are not independent. The shift to the service sector is intimately linked to the process of increasing metropolitan concentration, which also contributes to the obsolescence of rural areas and smaller centres. The purpose of these brief comments is to alert the reader to new information that may become available and to the way in which that might modify the existing forecasts. The widely recognized metropolitanization of Canada raises serious questions on the spatial distribution of economic growth. As discussed above, the population forecasts presented here often submerge the question of what the city is spatially. By the year 2001 we will undoubtedly have one continuous megalopolis stretching from Oshawa to St Catharines. To forecast the future population of this megalopolis, should we merely add up the component forecasts? The answer is not intuitively obvious. Furthermore there is the question of how to incorporate regional distributions of population into the individual forecasts. Most of the population forecasts in appendix B were derived for each city

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Urban futures for Central Canada

independently and therefore cannot take into account the interrelationship between large CMAs and small MUAs. If Toronto experiences the upper bound projected population, is this consistent with high growth rate of the smaller MUAs? One link in this problem is migration. Migrants may be very selective and respond quite strongly to the anticipated structural changes (see paper 5). The post-industrial society has been described as one where the service sector is the predominant centre of economic activities. This shift in the occupational structure will have a strong effect on the rearrangement of population and economic activity within metropolitan areas. Paper 6 below suggests that urban areas with high employment in the service and professional sector received large numbers of in-migrants in the 25-44 age range. The final structural change identified above is the obsolescence of some urban and rural areas. This is a difficult process to handle in direct population forecast since these are based largely on demographic trends. Obsolescence refers primarily to economic conditions. Forecasts which are derived from indirect procedures would be more successful and less prone to ignore this process/ since the forecasts are built on the projected economic demands of the urban area. NOTES 1

2

3

At present we are suffering from the reverse error, declining school enrollment resulting in embarrassed politicians and administrators who have over-built their institutions on the basis of forecasts made 10 to 15 years ago. The inherent difficulties of social values and goals and their definition preclude its use in Canada, at least in the near future (see paper 11 by Blumenfeld in this volume). As most of the data compilation and analysis in this volume preceded publication of the 1971 Census, the statistics and forecasts generally refer to the 1966 definitions of urban areas. As of 1971 there were 9 metropolitan areas in Ontario and 3 in Quebec (see table I.I). The major urban area category was replaced in the 1971 Census by the census agglomeration. These definitional changes pose a severe limitation on the establishment of consistent time series data for input to forecasting models.

Long-range employment forecasting 4

5

79

It is surprising that in so many instances the authors of forecasts have failed to consider the possible effects of differing assumptions on the location of urban boundaries. This oversight is particularly acute in the more densely populated areas of the country, such as in southern Ontario and Quebec, where rural densities are high and towns are located in close proximity. In areas of low population density, northern Ontario for example, boundary problems are of little significance. This consistency is inherent in the methodology used in generating the forecasts since there is really no means for generating variations in in-migration rates among cities. If one grows (as the province grows) all grow. No forecasts are yet available which examine, for example, the impact on all other places of constraining Toronto's growth while Ontario's population continues to grow.

REFERENCES Isard, W. 1960. Methods of Regional Analysis. New York: Wiley Lithwick, N.H. 1970. Urban Canada: Problems and Prospects. Ottawa: CMHC Stone, L. 1967. Urban Development in Canada. Ottawa: Dominion Bureau of Statistics

4 Long-range employment forecasting for the Toronto metropolitan region* JOHNR.MIRON A CONCEPTUAL FRAMEWORK Planning at the regional level, for both public and private facilities, requires some expectations about the future. Predictions about the dimensions of future socioeconomic structures are an important component of these expectations. An interesting dimension in this regard is the anticipated level of employment, the significance of employment forecasts lying primarily in what these imply in terms of broad

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Urban futures for Central Canada

economic, ecological, and social impacts on the region. Almost all planners, private and public, social or physical, need and use employment forecasts even though these may be for a number of different purposes. It is not difficult to describe a broad range of possible employment forecasts (figure 4.1). One can imagine extreme situations in which regional employment might increase or decrease rapidly from the present base year to a projection or target year. This affords a range of employment forecasts that likely includes the actual level of employment when the target year arrives. Generally, however, this forecast range is too wide to be of value to the planner; he must usually have a more constrained range of forecasts.

Figure 4.1 There are several methods of constraining this range of regional employment forecasts. One might first attempt to limit the range by assuming that some weighted average of past growth rates is the expected growth rate over the projection period. While use of such a procedure may result in a single-valued forecast rather than a range of forecasts, there are too many changing conditions to make such an assumption acceptable. A second method is based on the relationships between employment and other variables in the socioeconomic system. These relationships may or may not be quantifiable, but, if one can both predict the future values

Long-range employment forecasting

81

of these other variables and the future form of their relationship to employment, an employment forecast range can be derived. Three implications follow immediately from the implementation of this latter method. First, in order to understand the relationships between employment and other variables, there must be a set of hypotheses (a model) linking these variables. Any number of valid models can be used, but we require an operational one. A second implication is that the set of other variables and their relationships to the employment variable in this model must themselves be more predictable than the employment variable. The third implication is that a choice must be made between a macro model (collective behaviour) and a micro model (individual behaviour) . A micro model is generally preferable in theoretical terms, but often a lack of adequate data and theoretical constructs necessitates the use of a macro model. OVERVIEW OF THE METHODOLOGY AND METHOD In this study we attempt to make long-range employment forecasts for the Toronto census metropolitan area (1961 areal definition). The projection period ranges from 1971 to 2001 and the employment forecasts are made for each of sixty-four commercial and non-commercial industry sectors (see Miron, 1972, for technical details). The second forecast-constraint method, discussed above, was chosen for this study. Models are formulated in macro terms to relate employment by industry sector to a set of other relatively predictable exogenous (independent) variables. The adoption of a set of models, which can be termed a method, presumes the development of a rationale, or methodology (figure 4.2). Regional employment forecasts are undertaken using a two-phase method. National employment by sector is forecast in phase one, and the regional share of that growth is forecast in phase two. Since these method phases are undertaken sequentially, it is assumed that the nation will grow without regard to the rate of growth in the study region. Thus the region is seen to share in the national growth without helping to cause it. This, of course, is a simplification of reality but has the merit that it permits the resolution of a complex forecasting problem into two somewhat less complex and independent subproblems.

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Urban futures for Central Canada

Figure 4.2 Regional employment forecasting methodology in schematic form DETAILED METHODOLOGY, METHOD, AND INTERPRETATION:

PHASE ONE

Consider phase one, the prediction of national employment by industry sector. Employment may be related to the level of output of an industry sector. The level of output may usefully be partitioned into final and intermediate demand outputs. The significance of this is that final demand by consumers, investors, exporters, and government, is seen to be exogenous, while intermediate demand, by other industry sectors, is seen to be related to the levels of final demand faced by those sectors. Thus the output of an industry sector is seen to be related to the relative sizes of the various final demand component aggregates (personal consumer expenditures, government current expenditures, investment, and net exports) and to the distribution of each of these aggregates among all the industry sectors. These relationships can be expressed schematically as follows:

where E is the vector of employments by industry sector; O is the vector of outputs by industry sector; ID is the vector of intermediate demands by industry sector; FD is the vector of final demands by industry sector; CIG is the vector of final demand component aggregates; and DSTN is the matrix of final demand percentage distributions by component and industry sector.

Long-range employment forecasting

83

1

Forecasting gross national expenditure and component aggregates A long-run econometric growth model can be used to forecast both gross national expenditure (GNE) or total final demand and its component aggregates. The importance of these forecasts is two-fold. First, the overall level of GNE affects the total level of employment. Second, the kinds of demands placed upon each industry sector will change if the relative size of each component aggregate is changing over time. This latter point states nothing more than that if, for example, less is spent in Canada on investment and more on consumption and government expenditures, then there will obviously be a decline in the demand for such commodities as heavy capital goods, at least in the short-run. A long-run econometric growth model for Canada has been constructed by Brown (1964) in work for the Royal Commission on Health Services. This model was adopted for our study both because Brown had already used it for long-range predictions, and because of its relative simplicity. It is a relatively simple matter to revise and extend his input variable forecasts. The predictions of GNE and its distribution among component aggregates, derived using these revised inputs, are summarized in table 4.1. By using the model forecasts are derived which indicate a relative decline in personal consumer expenditures (PCE) and increases in the other two components, government expenditures and investment. TABLE 4.1 Summary of GNE and component distribution predictions, Canada, 1971-2001

Gross national expenditure (GNE) (billions of 1957 dollars) Personal consumer expenditure (% of GNE) Government current expenditure (% of GNE) Investment (% of GNE)

1971

1981

1991

2001

67

115

214

418

57.0

57.7

54.4

52.4

16.9 26.9

17.7 24.7

19.1 26.1

20.4 27.1

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Urban futures for Central Canada

Anticipating future results, one might thus expect a relative decline in employment in those industry sectors which cater most specifically to consumer goods. 2 Forecasting component distributions It is quite difficult to handle the problem of predicting the components' distributions among the industry sectors because of the lack of detailed data. The one exception is in the personal consumer expenditures (PCE) component which fortunately accounts for about 60 per cent of all GNE. The method used here involves the taking of a weighted average of the base-year (1961) percentage distribution of the PCE component aggregate among the industry sectors and a longrun percentage distribution. The long-run percentage distribution is derived from work done by Schweitzer (1970, 1971) on consumption functions for the Economic Council of Canada. A summary of the base-year and long-run distributions is presented in table 4.2.1 The trends in the largest of the GNE components are startling in size although expected in terms of direction. Principally the movement in consumer expenditures is away from foodstuffs and manufactured goods and towards rents, home ownership, travel, and personal services (notably medical care). The projected relative declines in trade and the unallocated groups are attributable to this shift from 'hard1 goods to 'soft1 services. Using the predicted GNE component aggregates and the predicted component percentage distributions, one can calculate the final demand forecast associated with each industry sector. A weighted average of the 1961 and long-run percentage distributions is used for the personal consumer expenditures component and the 1961 distributions are used for the other components. The GNE distribution forecasts so obtained are summarized in table 4.3. Reflected in these forecasts are the shifts both within the PCE distribution and from PCE to government current expenditures and investment. 3 Forecasting national industry outputs The relationship between the final demand of an industry sector and the level of output it achieves is a complex one. Basically the output of a sector is the amount required to meet its final demand plus the amount it supplies to other industry sectors to enable them to meet their final demands.

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85

TABLE 4.2 Summary of 1961 and long-run percentage distributions of personal consumer expenditures among industry groups Group (sectors)

1961

Long-run

Primary products (1-7) Food and tobacco (8-17) Clothing and textiles (18-24) Manufactured goods (25-53) Construction (54) Trade (55) Transport and utilities (56-8) Business and financial services (59, 60) Personal services (61, 62)

2.21 14.79 6.30 12.71 0.04 16.67 6.07 19.14 10.49

1.04 6.85 3.40 15.51 0.25 13.20 10.53 23.55 15.42

Unallocated

11.55

10.25

100.00

100.00

TOTAL

NOTE The unallocated row is sum of rows 63-75 in the input-output table for Canada. Major items include transport and commodity tax margins.

TABLE 4.3 Summary of final demand by industry group, Canada, 1961 and forecasts to 2001 Industry group (sectors)

Primary products (1-7) Food and tobacco (8-17 Clothing and textiles (18-24) Manufactured goods (25-53) Construction (54) Trade (55) Transport and utilities (56-58) Business and financial services (59,60) Personal services (61, 62) Unallocated TOTAL

1961 1981 2001 (billicms of 1961 dollars)

1

3

7

4 1 6 6 5 3 5 2

8 2 18 18 13 8 17 10

21 7 79 69 41 27 59 37

7

24

•97

40

121

444

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Urban futures for Central Canada

For 1961 the input-output table for Canada provides a snapshot of these interindustry intermediate demands at one point in time. If it is assumed that these flows remain constant in relative terms over the projection period, table 4.3 can be used to forecast outputs, given final demand, by industry sector. The projections thus derived are summarized in table 4.4 and, in general, reflect the basic thrust of the final demand projections. The derivation of industry outputs is important because, although they are endogenously generated by the distribution of final demands, they, and not the final demands, form the basis for the employment decisions among the industry sectors. 4 Forecasting national employment Given the output distribution, the prediction of employment is equivalent to the prediction of output per employee (here referred to as productivity). From economic theory functions can be formulated which relate productivity to a number of other variables. A major constraint is posed here by severe data problems, but simple productivity models are formulated and statistically estimated for each of five major industry groups. These productivity projections are divided into the output forecasts to derive the employment forecasts. These employment forecasts for Canada are summarized in table 4.5. Differing productivity relationships for the various industry groups have resulted in employment forecasts with a starkly different distribution from that of the outputs. A slow growth in final demand for agriculture, combined with rapid productivity increases, has resulted in a shrinking of employment in the primary products group. The food, tobacco, clothing, and textiles sectors experience a decline because of falling final demands and moderate productivity gains. Employment in the manufactured goods sectors is predicted to increase at a slow rate for the same reason. Construction employment growth is reasonably vigorous, reflecting the increase in the investment component, although rapid productivity gains slow the growth of employment in this sector. The trade, transportation, and utilities sectors experience rapid and sustained growth, principally because of slow productivity increases, and slightly increase their shares of total employment by 2001. The business and financial services group experiences slightly greater increases, and the personal services sector's employment is

Long-range employment forecasting

87

TABLE 4.4 Summary of output by industry group, Canada, 1961 and forecasts to 2001 Industry group (sectors)

1961 1981 2001 (billic3ns of 1961 dollars)

Primary products (1-7) Food and tobacco (8-17) Clothing and textiles (18-24) Manufactured goods (25-53) Construction (54) Trade (55) Transport and utilities (56-58) Business and financial services (59, 60) Personal services (61, 62)

6 6 3 15 7 7 6 8 4

15 12 6 55 22 19 18 23 13

48 34 20 218 81 63 62 81 47

TOTAL (1-62)

62

183

654

TABLE 4.5 Summary of employment by industry group, Canada, 1961 and forecasts to 2001 Industry group (sectors)

1961 1981 2001 (thousands of persons)

Primary products (1-7) Food and tobacco (8-17) Clothing and textiles (18-24) Manufactured goods (25-53) Construction (54) Trade (55) Transport and utilities (56-58) Business and financial services (59, 60) Personal services (61, 62)

857 221 236 1172 303 761 586 264 351

958 244 265 1682 524 1517 1274 590 893

814 202 253 1894 610 2264 1873 927 1451

869

2799

4726

5620

10746

15014

Non-commercial services (63, 64) TOTAL

NOTE Non-commercial services includes health, education , welfare, and community services, as well as government .

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Urban futures for Central Canada

forecast to rise quickly in the face of rapid output, and slow productivity increases. The non-commercial services group grows the most quickly of all, reflecting an increasing orientation toward non-commercial services - health, education, and welfare. DETAILED METHODOLOGY, METHOD, AND INTERPRETATION:

PHASE TWO

In phase two the share of national employment occurring in the region is predicted and applied to the national employment forecasts to derive regional employment forecasts. A macro model approach is taken with regard to the explanation and projection of the share of national employment occurring within the region. The basic hypothesis used here is that the employment share of an industry sector is principally related to the share of national population occurring within the region. 1 Regional employment and population shares A positive relationship is hypothesized between population and employment shares. In this view the population share is thought of as a simple proxy for the share of national demand occurring within the region. Thus the population share affects the revenues of an industry sector, making the relationship between population and employment shares positive. However there are conditions under which the employment share might be expected to fall as the population share increases. Two general conditions may be identified. First the population share may act as a proxy for variables which are positively related to the costs incurred by an industry sector. As an example, the population share may be positively correlated with the density of development, the price of land, and congestion, all of which serve to increase an industry's costs of operation. Second for some industry sectors the population share may not be a suitable proxy for demand and may even be negatively related to demand. This is most likely to be true of those sectors for which (i) final demand is small relative to intermediate demand, and (ii) consumer demand is a small part of final demand. It is difficult to ascertain, a priori, whether a particular industry sector will respond positively or negatively to population share increases. It may well be that the only satisfactory test is empirical consistency. In that case a

Long-range employment forecasting

89

relationship derived for an industry sector here has to be regarded as preliminary until similar measurements can be derived for other regions. 2 Regional employment and national unemployment rates This fundamental relationship between population and employment share, be it positive or negative, may be affected by general economic conditions. Consider, for instance, a multi-plant firm with a plant in the study region and other plants scattered elsewhere. Suppose that this firm faces an increased demand, a 'boom1 period, which it perceives to be short-lived. The firm seeks a strategy for coping with this short-term increase in demand. Should it expand its plant in the study region or expand another plant elsewhere? The choice for a profit-maximizing firm would depend in part upon the production functions associated with each plant. There is no reason to expect, intuitively, that employment in each plant would be increased proportionately. However, if the employment is not increased proportionately, there will be a change in that industry sector's employment shares in the various regions. When the expansionary period is over, these employment shares will return to their original levels. A converse argument might be applied to the behaviour of employment shares during recessionary periods. Furthermore in a competitive situation the behaviour of a number of single-plant firms should be similar to that of the profit-maximizing multi-plant firm. In both cases it seems reasonable to expect some relationship between general economic conditions and the employment shares of any sector. Again it is difficult to specify, a priori, Whether a particular industry sector will display a positive or negative relationship between employment shares and business conditions. There are a number of measures of general economic conditions which might be used in this model. Most such measures relate to the rate of capacity utilization of either labour or capital. The national unemployment rate is chosen for this study because of its availability and simplicity. Over the 1951-69 period, for which the model is to be evaluated, labour unemployment rates seem to have been a reasonable reflection of general economic conditions. 3 Regional employment and adaptive behaviour Finally the employment-share model cannot be expected to change immediately and exactly as the population share and

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Urban futures for Central Canada

unemployment rate change. The various firms in the industry sector make output and employment decisions independently and in view of their own perceived future needs. These firms may be consistently optimistic and collectively overshoot their desired employment share regularly. On the other hand, they may be cautious and just as consistently undershoot their desired employment level. By desired share we mean the share that the industry sector will tend toward, given a fixed population share and unemployment rate, over the long run. The simplest kind of model which allows for under- and over-shooting is the adaptive adjustment model,

where St is the employment share in year 't1; X is a constant; and S-f- is the desired employment share; it is given by

where P^ is the population share in year ' t' , and U-t is the unemployment rate in year ' t'. An adaptive adjustment model is statistically estimated for each of the industry sectors using historical series for each variable. 4 Forecasting regional employment shares These models are then used recursively to predict future values for the employment shares. In other words Sj- is predicted given predictions of P£, [7t, and St-i- The population share projections P£ are taken from a demographic study undertaken by the Metropolitan Toronto Planning Board. The unemployment rate (U^) projections were assumed to fall to 4.5 per cent by 1973 and to remain there through 2001.2 The projections derived for the industry sector employment shares are summarized in table 4.6. These projections contain a number of surprises. The primary products share declines, reflecting the withdrawal of agriculture from the region. The food and tobacco share falls through to 1981 and then levels out. The clothing and textiles share falls from 1961 to 1981 and then rises to 2001 because of the contrasting trends in the declining clothing and rubber sectors and the rising leather and textiles activities. The employment share for manufactured goods is the fastest rising of all. The strongest sectors

Long-range employment forecasting

91

TABLE 4.6 Summary of regional employment shares for the Toronto census metropolitan area, 1961-2001 Industry group (sectors)

1961

Primary products (1-7) Food and tobacco (8-17) Clothing and textiles (18-24) Manufactured goods (25-53) Construction (54) Trade (55) Transport and utilities (56-58) Business and financial services (59, 60) Personal services (61, 62)

0.5 14.5 14.4 14.3 13.2 17.6 9.7 27.3 15.1

0.4 13.1 12.8 19.4 16.0 15.7 11.8 27.5 13.7

Non-commercial services (63, 64)

13.3

11.7

13.7

OVERALL

12.6

13.8

14.8

1981 (per cent)

2001

0.4 13.4 14.2 21.1 16.1 14.2 14.4 27.0 11.4

in this group are diverse; furniture and fixtures, paper products, structural metals, aircraft and parts, motor vehicles, communications equipment, miscellaneous electrical products, non-metallic mineral products, and plastics and synthetic resin products. This strong growth in regional concentration contravenes one conventional wisdom which sees the large metropolitan region as becoming less and less a manufacturing centre. The historical trend of the increasing important of Toronto as a manufacturing centre is predicted to continue. The construction share will rise moderately over the forecast period, while trade and personal services are predicted to fall, reflecting a long historical trend in this direction. The transportation and utilities share is slated to increase dramatically, although the communications sector in this group is predicted to remain constant. The dominance of the business and financial services group in the Toronto CMA relative to other regions is expected to continue, although no increase in the region's share of national employment is forecasted. 5 Forecasting regional employment Predictions of the region's actual employment levels are derived by multiplying the employment shares projections of table 4.6 by the national employment predictions of table

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Urban futures for Central Canada

4.5 (see table 4.7). The observed trends are the result of the interactions of the national trends in employment with the regional trends in employment shares. TABLE 4.7 Summary of employment in the Toronto census metropolitan area, 1961-2001 Industry group (sectors)

1961 1981 2001 (thousands of p 0, a > 0, a < 0, a < 0, and a < 0. The variables are growth rates and thus are unit free, except for accessibility which is measured in hours of driving time. EMPIRICAL METHOD The model is estimated by a cross-section regression analysis of several stratifications of the sample of urban areas in Ontario and Quebec. The use of cross-sectional data implies that each urban area of a particular class is assumed to be

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Urban futures for Central Canada

an independent observation of a hypothetical urban area in that class. Urban areas differ only in the levels of the explanatory variables, and this variation accounts for the variation in the dependent variable. If there were explicit stages of urban growth, then this factor would be missed in the model. Stratification of the sample The urban system hierarchy is defined primarily in terms of Simmons's map of the largest outflow of business-originated telephone calls from each location (Simmons, 1972), which is generalized and extended in the frontispiece of this volume. The map presents a well-defined hierarchy with some striking patterns. The urban areas are divided into two clearcut systems centred on Montreal and Toronto, with Ottawa included in the Montreal system. Hamilton serves no major function as a regional centre, but appears to act as a part of Toronto, with Toronto's largest outflow going to Hamilton and Hamilton's largest outflow going to Toronto. Using this map in conjunction with others, Simmons concludes that 'Peripheral places (in terms of access to the whole system) are found at the geographical centre of the system, midway between the two poles (Kingston, Belleville)' (Simmons, 1972). Urban areas are classified into one of four levels in the urban system hierarchy. The two central places, Montreal and Toronto, are level 1. Level 2 includes urban areas with population greater than 50,000 which received the largest outflow of business calls from urban areas with population greater than 10,000, and which, in turn, directed their largest outflows to one of the two level 1 urban areas. Level 3, made up of satellite cities, consists of urban areas with population greater than 10,000 which are within less than two hours driving time from a level 1 or a level 2 urban area, and which have their largest outflow of business calls directed toward a nearby central city. Level 4, made up of independent cities, consists of urban areas with population greater than 10,000 which are two hours or more driving time from all level 1 and level 2 urban areas. The satellite city group should include all urban areas within the 'sphere of influence' of a central city, but far enough away from the central city that it does not contain a significant commuter population living in the satellite city and working in the central city. This study assumes that any urban area with a significant number of commuters would be

Growth and the urban hierarchy

103

included within the boundaries of the CMA or MUA as defined by Statistics Canada, although the continued decentralization of industry and population to the metropolitan periphery may have caused these 1961 definitions to be somewhat outdated. In fact the two satellite cities with the highest in-migration ratios are the closest to the Toronto-Hamilton CMA: Brampton and Georgetown, which have recently (1971) been redefined into the Toronto CMA.4 The final hierarchy is listed in table 5.1 and mapped in figure 5.1.5 The data Four types of data are used in this study:

in-migration,

TABLE 5.1 Urban system hierarchy for Central Canada

Urban area

Type of aggregation , if any

Hierarchical level

Toronto-Hamilton Barrie Brampton Brantford Cobourg Georgetown Lindsay Orillia Peterborough

MUA * * * * MUA

1 3 3 3 3 3 3 3 3

Kitchener-Waterloo Guelph

MA *

2 3

London St Thomas Sarnia Stratford Woodstock

MA *

MUA * *

2 3 3 3 3

St Catharines Niagara Falls Welland

MUA MUA *

2 3 3

Windsor Chatham

MA *

2

Fort William-Port Arthur (Thunder Bay)

MUA

4

MA * *

3

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Urban futures for Central Canada

Table 5.1 continued

Urban area

Type of aggregation , if any

MUA * * *

Hierarchical level

MUA MA MUA *

4 4 4 4 4 4 4 4

Montreal Drummondville Granby Joliette St Hyacinthe St Jean St Jerome Valleyfield

MA MUA * * * MUA * MUA

1 3 3 3 3 3 3 3

Ottawa Brockville Cornwall

MA * *

2 3 3

Quebec Thetford Mines

MA *

2 3

Sherbrooke Magog Victor iaville

MUA * *

2 3 3

Trois Rivieres Shawinigan

MUA MUA

2 3

Alma Rimouski Riviere du Loup Rouyn Sept lies Val d'Or

* * * * * *

4 4 4 4 4 4

Kingston North Bay Owen Sound Pembroke Sault Ste Marie Sudbury Timmins Trenton

NOTES MA = metropolitan area; MUA = major urban area (1966); * = municipal city boundaries

Figure 5.1

The urban hierarchy

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Urban futures for Central Canada

municipal expenditures, manufacturing employment, and accessibility (table 5.2). The migration data cover the period 1956-61; the manufacturing and municipal data are growth variables, representing annual growth rates between 1956 and 1959. It would appear that the data for the explanatory variables are in a sense lagged behind the dependent variable. 6 By lagging the explanatory variables the causes or direct linkages resulting in in-migration, rather than the results or the effects of an urban area's migratory experience, should be revealed. Regression methods Regression coefficients are to be estimated for each of the four levels of stratification of the sample, for particular TABLE 5.2 Data for each urban area in the analysis of growth

TorontoHamilton KitchenerWaterloo London St Catharines Windsor Barrie B ramp ton Brantford Cobourg Georgetown Lindsay Orillia Peterborough Guelph St Thomas Sarnia Stratford Woodstock Niagara Falls

Level

Percentage annual growth rate in Migration manuf ac tur ing employment ratio R E

Percentage annual growth Auto driving rate in municipal time expenditures (hrs) T M

1

0.0773

0.98

13.83

0.0

2 2

0.1380 0.1570

1.38 0.26

10.89 13.14

1.115 1.900

2 2 3 3 3 3 3 3 3 3 3 3 3 3 3

0.1199 0.0579 0.2701 0.3343 0.0972 0.2147 0.4194 0.1593 0.1258 0.1378 0.1413 0.1181 0.1539 0.1199 0.1622

-2.98 -11.04 8.32 10.34 0.76 1.34 0.36 4.64 10.24 -2.01 0.75 2.55 -0.66 -5.68 1.30

9.95 8.44 14.86 12.54 9.25 10.00 26.35 6.69 11.58 11.49 9.71 7.31 12.69 6.74 12.98

0.933 4.167 1.267 0.625 0.850 1.597 0.845 1.763 1.727 1.843 0.320 0.360 1.240 0.760 0.510

3

0.1147

-5.13

14.49

0.200

Growth and the urban hierarchy

107

Table 5.2 continued

Welland Chatham Thunder Bay Kingston North Bay Owen Sound Pembroke Sault Ste Marie Sudbury Timmins Trenton Montreal Ottawa Quebec Sherbrooke Trois Rivieres Drummondville Granby Joliette St Hyacinthe St Jean St Jerome Valleyfield Brockville Cornwall Thetford Mines Magog Victoriaville Shawinigan Alma Rimouski Riviere du Loup Rouyn Sept lies Val d'Or

T

Level

R

E

M

3 3 4 4 4 4 4

0.0900 0.1388 0.1116 0.1880 0.2057 0.1087 0.1551

-5.44 -2.00 -3.65 -4.81 3.78 -8.00 1.50

11.62 15.64 10.42 13.62 13.02 2.95 11.83

0.300 0.907 17.687 3.457 4.327 2.318 5.103

4 4 4 4

0.1110 0.1082 0.1137 0.2325

1.36 2.70 -5.17 -1.61

16.20 8.82 5.59 12.36

8.927 5.207 8.807 2.257

1 2 2 2

0.0681 0.1519 0.0753 0.1338

-0.77 -2.52 0.81 -4.24

13.91 9.84 11.02 8.84

0.0 2.520 3.320 1.940

2

0.1088

-2.07

8.10

1.980

3 3 3 3 3 3 3 3 3

0.1029 0.1364 0.1055 0.1407 0.1697 0.1404 0.1018 0.1535 0.1034

-0.63 1.76 -2.02 -1.13 3.19 1.06 -3.65 0.39 8.91

16.52 12.42 10.62 10.51 15.70 13.01 9.41 10.07 42.23

1.420 0.900 0.820 0.820 0.560 0.520 0.680 1.440 1.400

3 3

0.0725 0.0972

-8.60 -4.36

13.88 10.94

1.640 0.340

3 3 4 4

0.1139 0.0890 0.0809 0.1601

-3.45 -3.99 8.48 2.10

14.85 11.08 37.42 15.69

1,120 0.360 5.780 7.120

4 4 4 4

0.0646 0.1455 0.4530 0.1553

-5.62 9.54 4.75 -9.73

8.64 11.34 33.97 7.62

5.820 7.520 8.600 6.300

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Urban futures for Central Canada

combinations of levels, and for differences between the two regions centred on Toronto and Montreal. The sample is thus divided according to the schema in table 5.3, with the specified number of observations in each category. Due to the small number of observations in levels 1 and 2, the two categories are combined into a level 1-2, with ten observations. Coefficients are then estimated for each of the two regions for the following categories of the hierarchy: levels 1, 2, 3, 4; level 1-2; level 3; level 4; and level 3-4. TABLE 5.3 Stratification of the sample into regions and systems of urban areas

Regions Toronto-centred region Montr eal- centred region TOTALS

Urban system hiesrarchy Level 3 Level 1 Level 2

1

4

1

4

2

8

Level 4

TOTALS

9

30

13

6

24

29

15

54

16

The numbers represent the number of urban areas in each category.

EMPIRICAL FINDINGS

Results for the Toronto- and Montreal-centred regions Table 5.4 presents the results for the Toronto-centred region, and table 5.5 for the Montreal-centred region. The model makes specific assumptions as to the signs of the coefficients in equation 1, so that the appropriate test of significance is a one-tailed t-test. If an estimated coefficient was not significantly different from zero at the 0.05 level of significance, then the value of the coefficient is assumed to be zero in constructing tables 5.4 and 5.5. The results for satellite cities in the Toronto-centred region are shown in table 5.4 (level 3 ) , Growth in employment and municipal expenditures appear to have had the same effect on urban growth. If these two variables are assumed to be proxies, then the supply and demand factors play an equal role in generating urban growth for satellite cities in the Toronto-centred region. Comparing this result with

TABLE 5.4 Regression (OLS) coefficients of the reduced form equation of urban growth (rate of in-migration) in Toronto-centred region

Explanatory variables Leval in the urban hierarchy

Constant

Manuf . emp . growth (E)

Municipal expenditure growth (M)

T •E

1, 2

0.073 (0.009)

0.0

-

0.0

1, 2

0.305 (0.167)

-

0.0

-

3 4

0.0

0.393 (0.068)

2.042 (0.467) 3.600 (0.643)

2.392 (0.745) 0.0

T •M

Accessibility (T) 0.0

0.0

-1.238 (0.415)

0.0

-0.831 (0.136)

0.0

-0.145 (0.060) 0.0

-0.069 (0.014)

NOTE Numbers in parentheses are the standard errors of the estimated coefficients significantly different from zero at the 5 per cent one-tail level. The line (-) indicates that this variable did not enter the regression due to the small sample size of the level 1, 2 urban areas. 1

For definitions, see text.

TABLE 5.5 Regression (OLS) coefficients of the reduced form equation of urban growth (rate of in-migration) in the Montreal-centred region

Explanatory variabtles Level in the urban hierarchy

Constant

Manuf . emp . growth (E)

Municipal expenditure growth (M)

If 2

0.073 (0.009)

0.0

-

If 2

0.305 (0.167)

-

0.0

3

0.260 (0.103)

2.042 (0.467)

0.0

4

0.393 (0.068)

16.664 (3.254)

0.0

T •E

T •M

-2.372 (0.729)

-

Accessibility (T)

-0.041 (0.009) 0.0

-0.145 (0.060

-1.238 (0.415)

0.0

0.0

-2.448 (0.471)

0.0

-0.069 (0.014)

NOTE Numbers in parentheses are the standard errors of the estimated coefficients significantly different from zero at the 5 per cent one-tail level. The line (-) indicates that this variable did not enter the regression due to the small sample size of the level 1, 2 urban areas. 1

For definitions see text.

Growth and the urban hierarchy

111

table 5.5 (level 3), the effect of growth in manufacturing employment on urban growth is the same for both regions. However growth in municipal expenditures is not a significant explanatory variable for urban growth in satellite cities in the Montreal-centred region. Although accessibility alone does not play a role in generating growth in satellite cities in either region, it does interact with growth in manufacturing in both regions. It thus entered as a significant variable for satellite cities via this effect. The results for independent cities are also presented in tables 5.4 and 5.5 (level 4). Here accessibility does enter as a significant variable, with both absolute and interaction effects. In neither region does growth in municipal expenditures enter as a significant variable generating urban growth. Apparently only demand forces and accessibility are important as sources of growth for independent cities. A 1 per cent growth in manufacturing employment, for instance, would have resulted in a little over four times as much growth in independent cities in the Montreal-centred region as in the Toronto-centred region. Unfortunately, because of the small number of combined level 1-2 urban areas in the sample, it has not been possible to fit the entire model for this level of the hierarchy. Consequently the model is split into the supply and demand components and the resulting equations estimated for level 1-2. The results are presented in tables 5.4 and 5.5. The constant term is the same for both the Montreal- and Toronto-centred regions, although it is different in the two equations within each table. In the equation measuring the supply determinant of growth accessibility is significant and there are no regional differences; but, in the demand equation accessibility is not significant in the Toronto-centred region, while it is significant in the Montreal-centred region. Furthermore it interacts with the employment factor in generating growth. When the Toronto- and Montreal-centred regions are compared at each level, patterns seem to hold across the urban hierarchy. Growth in municipal expenditures does not play any role in generating growth in the Montreal-centred region at any level of the hierarchy. Employment appears to play a stronger role in influencing growth in the Montreal- than in the Toronto-centred region, and it appears to play a stronger role in independent cities than in satellite cities. If the government were to attempt to encourage growth by subsidizing municipal services uniformly across all urban

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Urban futures for Central Canada

areas in Ontario and Quebec, it would achieve its desired effect only in satellite cities in the Toronto-centred region. Apparently other cities would be unaffected. Test of the urban system hierarchy The results discussed above argue that the form of the growth model is affected by position in the urban system hierarchy. It is possible to test this hypothesis directly in one instance. Because of the problem of the small sample size of level 1-2 urban areas, the test of the significance of position in the hierarchy is conducted only between level 3 and level 4 urban areas. An analysis of variance test was performed and resulted in an F-statistic of F(i2,20) = 2.82. This is significant at the 0.025 level, suggesting that the sample should be stratified into satellite and independent cities. Since the estimated coefficients are different for these two levels, and the stratification is significant, the form of the growth model will differ according to the position in the urban system hierarchy. IMPLICATIONS FOR THE FUTURE The Canadian economy has shifted from one based primarily on industrial activity to one where the majority of employment is now in the service sector. The findings of this study can be used to interpret the possible effects of this structural shift on the population forecasts presented in part I. In only one case, satellite cities in Ontario, is the growth in municipal expenditures a significant factor in generating urban growth. If we accept this variable as a proxy for the service sector, the above findings suggest that the urban growth rate for these cities may be higher than forecasted. Since the service sector appears to play very little role in generating growth in the province of Quebec, a lower than average forecast for future population growth for cities in Quebec is indicated. The results of this study also reveal other differences between Ontario and Quebec. One such difference concerns the effect of the growth in manufacturing employment in generating growth in independent cities. This variable is much stronger in Quebec than in Ontario. If the independent cities in both provinces face the same growth in aggregate demand conditions, and thus experience the same growth in manufacturing employment, the independent Quebec cities will

Growth and the urban hierarchy

113

experience a higher relative urban growth rate than those in Ontario. This may well counterbalance the tendency with respect to the shift to the service sector (at least at the aggregate provincial level of population forecast), which will only reinforce the present contrast between Ontario and Quebec. Ontario has more satellite cities than Quebec, 18 to 11 (2 of the Ontario satellite cities, in fact, are classified as within the sphere of influence of the Montreal-centred region). In Ontario the satellite cities will become relatively more important, which will solidify the urban-metropolitan network of the Toronto-centred region, while in Quebec the independent cities may very well be the ones that become relatively more important, weakening the urban network of the Montreal-centred region. Both effects point to more dynamic urban growth in Ontario than in Quebec. The results of this study indicate that changes in both the transportation and communication links will affect the growth rate of cities in Central Canada directly and indirectly. Accessibility interacts with employment, making its effect on the city's growth rate felt through this factor for both satellite and independent cities in Central Canada. The forecasts presented in part I should also be modified with projected changes in the accessibility linkages in Central Canada. NOTES 1

2

3

4

Urban areas of this type are Barrie, Cobourg, Kingston, Ottawa, Pembroke, Rouyn, St Jean, and Trenton. These urban areas appear to be scattered fairly evenly throughout the different levels of the urban hierarchy as defined here. Urban areas of this type are Fort William (Thunder Bay), North Bay, Riviere du Loup, Rimouski, Sept lies, Sault Ste Marie, Timmins, and Val d'Or. These urban areas all appear to be concentrated in one level of the urban hierarchy, independent cities, and in peripheral regions. This is a matrix of shortest driving times on existing roads between all urban areas with populations over 10,000 in Ontario and Quebec, developed by M.J. Hodgson for ongoing research at the Centre for Urban and Community Studies. Bunting (1972) also finds Brampton and Georgetown to be unusual cities in her study of 1961 cross-sectional

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Urban futures for Central Canada

characteristics. Her grouping procedure isolates these two cities in a group distinct from all others; she calls them Toronto satellites. She considers that this unusual effect is a result of the metropolitan expansion of Toronto between 1951 and 1961. 5 There are ten urban areas which fell so close to the boundaries of the subsystems that we made exceptions to the above decision rules. Since the metropolitan areas of Toronto and Hamilton are contiguous, we consider them to be one large metropolitan area. For driving time to the Toronto-Hamilton CMA we use the average driving time to both. According to the definition Stratford should be a satellite of Kitchener; since Stratford is almost equidistant from London and Kitchener, however, and London is the larger central city, we consider Stratford a satellite of London. Cobourg and Georgetown are not included in Simmons's sample; since they are less than two hours driving time from Toronto-Hamilton, we consider them satellites of Toronto-Hamilton. According to the definition Pembroke should be a satellite of Ottawa; since it is almost two hours driving time (1.91 hours) from Ottawa, and since it is 'midway between the two poles,' we consider it an independent city. The Eastern townships of Quebec are a particular problem. Victoriaville and Sherbrooke are both around two hours driving time from Montreal (2.12 and 1.94 hours respectively), and both have largest outflows of business calls to Montreal. Victoriaville is also 1.20 hours from Quebec City and 1.12 hours from Sherbrooke. Magog is not in Simmons's sample. Since Sherbrooke had a population of 70,253 in 1961 and is classified as an MUA by DBS, and Magog is 0.34 hours from Sherbrooke, we felt that, if Magog had been in Simmons's sample, it would have had largest outflows of business calls to Sherbrooke. Therefore we classify Sherbrooke as a level 2 urban area, with Magog as its satellite. Since Victoriaville is closest to Sherbrooke, we classify it as a satellite of Sherbrooke. 6 This is not entirely correct, since the migration data include people who had moved at least once in the period from 1956 to 1961. Consequently there is some overlap in time between the dependent and independent variables which could not be eliminated.

Growth and the urban hierarchy

115

REFERENCES Bunting, T. 1972. 'Dimensions and Groupings in the OntarioQuebec Urban System, 1951 and 1961,' in L.S. Bourne and R.D. MacKinnon, eds, Urban Systems Development in Central Canada: Selected Papers. Toronto: University of Toronto Press Davies, J.B. 1972. 'Behaviour of the Ontario-Quebec Urban System by Size Distribution,' in L.S. Bourne and R.D. MacKinnon, eds, Urban Systems Development in Central Canada: Selected Papers. Toronto: University of Toronto Press Dominion Bureau of Statistics. 1962. 1961 Census of Canada. Bulletin 1.1-6: Populations, Incorporated Cities, Towns and Villages. Ottawa: Queen's Printer Dominion Bureau of Statistics. 1969. 1961 Census of Canada. Bulletin SX-15: Population Sample, Characteristics of Migrant and Non-Migrant Population, Metropolitan Areas. Ottawa: Queen's Printer Dominion Bureau of Statistics. 1958. Manufacturing Industries of Canada 1956. Section G: Geographical Distribution . Ottawa: Queen's Printer Dominion Bureau of Statistics. 1961. Manufacturing Industries of Canada 1959. Section G: Geographical Distributions. Ottawa: Queen's Printer Dominion Bureau of Statistics. 1963. Revised Analytical Tabulation Programme for the 1961 Census Data on Population Movement. Ottawa: Queen's Printer Golant, S.M. 1972. 'Regression Models of Urban Growth in Ontario and Quebec,1 in L.S. Bourne and R.D. MacKinnon, eds, Urban Systems Development in Central Canada: Selected Papers. Toronto: University of Toronto Press Gujarti, D. 1970. 'Use of Dummy Variables in Testing for Equality Between Sets of Coefficients in Linear Regressions: A Generalization,' The American Statistician, 24/5: 1822 Lithwick, N.H. 1970. Urban Canada: Problems and Prospects. Ottawa: Central Mortgage and Housing Corporation Lithwick, N.H., and Paquet, G. 1968. Urban Studies: A Canadian Perspective. Toronto: Methuen Ontario Department of Municipal Affairs. 1957. 1956 Annual Report of Municipal Statistics. Toronto: Baptist Johnston Ontario Department of Municipal Affairs. 1960. 1959 Annual

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Urban futures for Central Canada

Report of Municipal Statistics. Toronto: Baptist Johnston Quebec Bureau of Statistics. 1956. 1954-1955 Financial Statement of School Corporations Quebec Bureau of Statistics. 1961. 1959-1960 Financial Statement of School Corporations Simmons, James W. 1972. "Interaction among the cities of Ontario and Quebec,1 in L.S. Bourne and R.D. MacKinnon, eds, Urban Systems Development in Central Canada: Selected Papers. Toronto: University of Toronto Press

6 The components of interurban migration streams MONTY WOODYARD

As the section on forecasting suggested, the most important unknown quantity in predicting population distributions is the amount and nature of migration. Assuming that the total current population is known, then to predict the population of some future date requires four measures: births, deaths, and in- and out-migration. When dealing with a reasonably closed spatial system, such as provinces or nations, the total future population can be estimated fairly accurately using the cohort-survival method. The four variables are either held constant, or simple assumptions are made about how they change over time. When attention is shifted to the distribution of population among cities within the urban system, however, these simple assumptions no longer suffice. Very little of the behaviour of an urban area can be explained by observing that area in isolation. The behaviour of the individual urban area as a point of origin and destination for migrants is determined by its interaction with the rest of the urban system. At the scale of the single urban area one can be reasonably confident of the assumptions regarding fertility and mortality rates, as they exhibit fairly continuous and predictable long-range trends. There is some evidence as well to suggest that out-migration may be a direct function of the age structure of the urban population (Lowry, 1966).

Components of interurban migration streams

117

However rapid fluctuations can be observed in the past behaviour of in-migration (Simmons, 1973). It appears that, of all the variables necessary for population forecasting, inmigration is the most sensitive to the properties of the urban system. And in dealing with in-migration it is important not only to be able to estimate the total number of inmigrants to an urban area, but also to identify the origin and age and sex breakdown, since these properties affect future rates of birth, death, and out-migration. In this paper characteristics of urban areas are related to levels of in-migration of various groups. There are two basic approaches possible. The first and more theoretical approach involves the postulation of a model of migration behaviour. According to the terms of the model key variables which are believed to determine migration behaviour are chosen. By statistical procedures one estimates parameters for those independent variables which in some specified combination will serve to best estimate in-migration rates (as in paper 5 and Courchene, 1970) . The second and more inductive approach, used here, begins with a large set of variables which may affect migration behaviour. The urban areas are grouped according to their in-migration rates. Variables are then chosen from the data set whose linear combinations best distinguish between highand low-migration groups of urban areas. A discriminant analysis is used to identify the variables which provide maximum discrimination among the groups and minimum probability of misclassification. THE ANALYSIS The urban areas are ranked according to their in-migration ratios, and divided at the mean to provide two groups. A set of variables describing the urban areas are developed; those variables whose linear combinations discriminate best between the two groups are identified. Statistical procedure A step-wise discriminant analysis selects variables from the data set and combines them into a discriminant function. At each step the variable giving the greatest decrease in the ratio of within to total generalized variance is chosen for the function. The coefficients of the discriminant function are estimated, and the urban areas are classified

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Urban futures for Central Canada

according to the value of the discriminant function. The process is repeated in a step-wise fashion until a specified minimum level of discrimination is reached. The coefficients of the final discriminant function are normalized, so that the values of coefficients within each function can be compared. The final form of the function is

where c is a vector of coefficients, x is a matrix of input variables, and p is the total number of variables included in the discriminant function. The data Two types of data are used for the discriminant analysis: in-migration data to classify the urban areas; and characteristics of the urban areas which are the input variables for the discriminant function. Census metropolitan areas, major urban areas, and other cities with populations over 10,000 in Ontario and Quebec in 1961 are examined. Migration data, obtained from a 20 per cent household sample taken in conjunction with the 1961 Census, are used (Dominion Bureau of Statistics 1962, 1969). The data include the number of migrants in each urban area from the three origin groups: the same province, different provinces in Canada, and abroad. The number of migrants in each of these three categories is broken down by sex and by four age groups (1524, 25-44, 45-64, and 65 and over). With three categories of origin, two sexes, and four age groups, the total migration stream to each city is therefore broken down into 24 components. Each of these components is expressed as a percentage of the total sample to produce a matrix of migration ratios. The sum of all of the 24 components of the migration stream is the total inmigration ratio for each urban area. The urban areas are ranked according to each of the 24 components of the migration stream, the totals for the three origin groups, and the total in-migration ratio. Each ranking is divided at its mean into high and low migration groups, and 28 separate discriminant functions are estimated, one for each grouping. The means and standard deviations of the migration variables are shown in table 6.1. The results of various components of the Urban Environment Study (Bunting, 1972; Golant, 1972; Barber, 1972) suggest several qualitative indices of functional, structural

Components of interurban migration streams

119

TABLE 6.1 Migration structure of the Central Canada urban system -total number of migrants in each category as percentage of total population

Components of the migration stream (code)

Male migrants from same province aged 15-24 (SP15M) Male migrants from same province aged 25-44 (SP25M) Male migrants from same province aged 45-64 (SP45M) Male migrants from same province aged 65 and over (SP65M) Female migrants from same province aged 15-24 (SP15F) Female migrants from same province aged 25-44 (SP25F) Female migrants from same province aged 45-64 (SP45F) Female migrants from same province aged 65 and over (SP65F) Male migrants from different province aged 15-24 (DP15M) Male migrants from different province aged 25-44 (DP25M) Male migrants from different province aged 45-64 (DP45M) Male migrants from different province aged 65 and over (DP65M) Female migrants from different province aged 15-24 (DP15F) Female migrants from different province aged 25-44 (DP25F) Female migrants from different province aged 45-64 (DP45F) Female migrants from different province aged 65 and over (DP65F) Male migrants from abroad aged 15-24 (FA15M) Male migrants from abroad aged 25-44 (FA25M) Male migrants from abroad aged 45-64 (FA45M) Male migrants from abroad aged 65 and over (FA65M) Female migrants from abroad aged 15-24 (FA15F) Female migrants from abroad aged 25-44 (FA25F) Female migrants from abroad aged 45-64 (FA45F) Female migrants from abroad aged 65 and over (FA65F)

Mean

Standard deviation

0.0113

0.0068

0.0256

0.0160

0.0071

0.0034

0.0021

0.0013

0.0152

0.0083

0.0229

0.0142

0.0069

0.0034

0.0029

0.0022

0.0020

0.0020

0.0048

0.0050

0.0010

0.0010

0.0003

0.0004

0.0024

0.0027

0.0042

0.0042

0.0008

0.0007

0.0004 0.0019 0.0059 0.0009

0.0004 0.0019 0.0050 0.0009

0.0001 0.0022 0.0056 0.0011

0.0002 0.0022 0.0046 0.0010

0.0003

0.0003

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Urban futures for Central Canada

Table 6.1 continued Components of the migration stream (code)

Mean

0.1240 Total migrants from same province (SPTOT) Total migrants from different province (DPTOT)0.0213 0.0236 Total migrants from abroad (FATOT) 1 0.1689 Total in-migrants (IMTOT)l

Standard deviation

0.0674 0.0198 0.0190 0.0836

NOTE Sample includes 63 urban areas of population 10,000 and over in 1961. See Britton (1972) for list of urban areas. SOURCE Dominion Bureau of Statistics (1963, 1968) 1 Includes migrants aqe 5-14 as well

growth, demographic, and locational characteristics of the urban areas. Nineteen variables are used as the data inputs to the discriminant analysis (table 6.2). Of the 19, 15 are based on the results of the previous research on the projects identified above. Scores on all of the first five economic indices range from zero to one, with low scores representing low employment in the respective occupational groupings. They are derived from a previous study by Britton (1972). Variable 6 is an index representing the level in the urban hierarchy and potential for accessing the major transportation and communications networks of the urban system. It ranged from zero to two, with low scores representing the top of the hierarchy and ease of access. A definition of the urban hierarchy similar to that discussed by Siegel (paper 5) is employed here. This index was broken down in the following manner: 0.0 0.001-0.999 1.000-1.199 1.200-1.999

level level level level

1: 2: 3: 4:

dominant central cities secondary central cities satellite cities independent cities

Variables 8 through 16 are factor scores on the various dimensions identified by Bunting (1972), and variable 19 is a dummy variable recognizing that the urban system of Central Canada is divided into two politically distinct provinces. For an urban area in Ontario it has a value of one; for an

Components of interurban migration streams

121

TABLE 6.2 Input variables for discriminant analysis

Variable name (code) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

Mean

0.3662 Economic function: Machinery (MA) 0.3134 Economic function: Mining (MI) 0.5587 Economic function: Service (SV) 0.2572 Economic function: Textiles (TX) 0.4475 Economic function: Paper and chemicals (PC) Access to urban hierarchy (UH) 1.0880 0.2214 Growth rate 1956-61 (GR) Growth rate stability (GS) 0.0016 Obsolescence (OB) 0.1719 0.0475 Cultural-linguistic characteristics (CL) 0.0716 Metropolitan status (MT) Commerciality (CM) 0.0232 0.0321 Peripherality (PR) Educational occupational characteristics (EO) 0.0444 0.0424 Growth characteristics (GC) -0.0317 Administration-defence industries (AD) 0.1198 Population 1961 (P2) 0.1004 Population 1956 (PI) 0.6032 Ontario-Quebec differences (OQ)

Standard deviation 0.1558 0.2194 0.1889 0.1478 0.1530 0.5018 0.2871 0.4870 0.8748 1.0109 1.0521 0.9810 1.0277 0.9223 1.0458 1.0309 0.3488 0.2882 0.4932

urban area in Quebec a value of zero. The means and standard deviations of all of the data input variables are shown in table 6.2. The correlation matrix for the input variables reveal 13 pairs of variables with r >± 0.50. The variables chosen by the discriminant analysis show what characteristics of urban areas have been associated with variations in migration rates. If the separations between groups are consistently large for a particular variable, one may infer that the migrants responded to this characteristic, but any conclusions which may be drawn must necessarily be inferential and exploratory. RESULTS Of the 28 discriminant functions produced, 17 were acceptable according to the dual criteria that the F-statistic for testing equality of group means over all included variables in both groups must be significant at the 0.001 level, and that the discriminant function must classify correctly at

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least 80 per cent of the urban areas in the sample. The coefficients and within-group means for the included variables in each of the 17 acceptable discriminant functions are shown in table 6.3. The input data perform poorly in discriminating between the high and low migration groups among migrants from within the same province. Only three of eight analyses are acceptable. The three acceptable functions reveal three common variable types. First are the economic variables, identifying urban areas with high employment in paper and chemicals (PC) receiving low numbers of in-migrants. Urban areas with high employment in services (SV) receive large numbers of males, aged 25-44, and urban areas with high employment in the professions (EO) receive large numbers of female migrants, aged 25-44. These data reflect the well-recognized shift in employment from the manufacturing to the service industries. The second common variables are the provincial, cultural, and linguistic variables (CL, OQ) with urban areas in Ontario receiving more migrants from Ontario than urban areas in Quebec receive from Quebec. The third common variables are the growth measures (GS, GC), with, as would be expected, rapidly growing urban areas receiving more migrants from the same province than slowly growing urban areas. The location variables (UH, PR) appear only in the function for males aged 25-44. However their effect is very strong in this function, occupying first and third place in order of importance. The remote, peripheral, independent cities receive large numbers of males aged 25-44 from other areas within the same province. The input data are much more satisfactory in discriminating between high and low levels of in-migrants from a different province, providing acceptable functions for five of the eight disaggregated components of migrants from a different province, as well as the function for total migrants. Again the economic variables are common throughout, with urban areas with high employment in manufacturing (PC, TX, MA) or trade and commerce (CM) receiving low numbers of migrants, and urban areas with high employment in services (SV, AD) receiving large numbers of migrants. The provincial, cultural, and linguistic variables (OQ, CL) are again common to all functions, with English-speaking urban areas receiving large numbers of migrants. Most functions for migrants from a different province also include a growth variable (GC, GS), with large numbers of migrants accruing to urban areas with

TABLE 6.3 Discriminant function coefficients and within-group means for selected migration streams Same Province, Males 25-44

Same Province, Males 45-64 Means

Low

Means

group

High group

UH 7.61 SV 6.58 PR -4.70 OQ 1.87 PC 1.40 CL -1.12 GS 0.57 No. urban areas

1.015 0.509 0.028 0.500 -0.214 -0.214 -0.078

1.215 0.645 0.040 0.783 0.385 0.501 0.140

40

23

F- value (df) Per cent misclassification

9.184

Variable

Coefficient

(7, 55)

12.7

Same Province, Females 25-44

Low Variable

Coefficient

group

High group

PC CL CG OB

2.86 0.24 -0.04 0.02

0.469 -0.169 -0.296 0.081

0.418 0.355 0.524 0.302

37

26

No. urban areas F-value (df) Per cent misclassification

7.306

(4,58)

19.0

Different Province, Males 15-24

Variable

Coefficient

Means Low High group group

PC GC EO CL

2.91 -0.49 0.16 0.13

0.478 -0.224 0.229 -0.106

0.395 0.505 -0.276 0.314

Low

Means

Variable

Coefficient

group

MA AD CL GC

3.65 -1.99 -1.32 -0.15

0.403 0.339 -0.207 -0.131

High group 0.302 -0.677 0.490 0.344

Table 6.3 continued 40

No. urban areas F- value (df) Per cent misclassification

8.343

23

(4,58)

19.0

Different Province, Males 25-44

Variable

Coefficient

F-value (df) Per cent misclassification

15.856

23 (4,58)

11.1

Different Province, Males 45-64

Means Low High group group

UH 5.14 MA 3.57 PI 2.71 TX 2.05 PC 1.68 GC -0.92 CL -0.45 No. urban areas

1.013 0.412 0.052 0.304 0.490 -0.135 -0.176

F- value (df) Per cent misclassification

16.756

40

6.3

40

No. urban areas

1.218 0.286 0.185 0.175 0.373 0.350 0.436

23 (7,55)

Variable

Coefficient

Means Low High group group

MA AD CL P2 GS

3.48 -2.31 -1.14 0.51 0.31

0.390 0.230 -0.171 0.062 -0.083

0.322 -0.520 a. 454 0.227 0.160

41

22

No. urban areas F-value (df) Per cent misclassification

7.844 19.0

(5,57)

Table 6.3 continued Different

Province, Females 15-24

Different

Variable

Coefficient

Means Low High group group

OQ

1.95 -1.44 0.99 0.88

0.500 0.318 -0.182 -0.090

0.810 -0.713 0.460 0.185

42

21

AD PR GS

No. urban areas F-value (df) Per cent misclassification

13.093

(4,58)

14.3

Coefficient

1.74 CL 0.80 MT -0.58 PR -0.53 CM No. urban areas

Coefficient

Means Lpw High group group

UH 6.76 MA 6.19 P2 4.15 AD -3.78 CL -1.48 GC 0.87 CS -0.83 No. urban areas

1.036 1.178 0.405 0,299 0.061 0.222 0.282 -0.577 -0.156 0.401 -0.176 0.423 -0.104 0.186 40 23

F-value (df) Per cent misclassification

10.885

(7,55)

7.9

From Abroad, Males 25-44

From Abroad, Males 15-24

Variable

Variable

Province, Females 25-44

Means Low High group group

Variable

-0.568 -0.206 0.288 0.211 33

CL 2.09 MT 0.83 AD -0.72 PR -0.57 No. urban areas

0.725 0.377 -0.249 -0.183 30

Coefficient

Means Low High group group -0.587 -0.159 0.165 0.265 34

0.791 0.342 -0.263 -0.241 29

Table 6.3 continued F-value (df) Per cent misclassification

21. 380

(4 ,58)

7.9

From AJbroad, Males 45-64

Variable

CL MT

Coefficient

1.65 0.70

F-value (df) Per cent misclassification

24. 581

(4,58)

11. 1

From Abroad, Females 15-24 Means High Low group group

-0. 605 -0. 187

0.766 0.356

No. urban areas

not available

F-value (df) Per cent misclassification

35. 209

(2,60)

15.9

From Abroad, Females 25-44

Variable

Coefficient

Means Low High group group

CL 1.79 MT 0.96 CM -0.67 No. urban areas

-0. 475 -0.211 0.227 37

F-value (df) Per cent misclassification

25.103

0.791 0.474 -0.267 26 (3,59)

11. 1

From Abroad, Females 45-64

Variable

Coefficient

Means Low High group group

CL MT GC

1.95 -0.86 0.67

-0. 263 -0. 199 -0.169

0.740 0.351 0.261

Variable

UH CL CM

Coefficient

1.93 0.60 0.09

Means Low High group group

1. 233 -0.453 0. 168

0.907 0.673 -0.158

Table 6.3 continued AD -0.49 No. urban areas

0.103 32

F-value (df) Per cent misclassification

23.198

-0.171 31 (4,58)

12.7

F-value (df) Per cent misclassification

35 15.602

28 (3,59)

11.1

All In-Migrants, Total

From Abroad, Total

Variable

Coefficient

Means Low High group group

CL MT PR

2.33 0.81 -0.45

-0.728 -0.177 0.238

0.799 0.312 -0.168

31

32

No. urban areas F-value (df) Per cent misclassification

No. urban areas

39.194 7.9

(3,59)

Variable

Coefficient

Means Low High group group

PC 3.79 AD -2.17 GC -0.45 CL 0.40 EO 0.28 No. urban areas

0.484 0.276 -0.242 -0.223 0.204 39

F-value (df) Per cent misclassification

12.050 14.3

0.388 -0.531 0.504 0.488 -0.215 24 (5,57)

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Urban futures for Central Canada

previously high and stable growth rates. Size of the urban area (PI, P2) is also important. The location variables (UH, PR) appear in five of the eight functions, with peripheral urban areas receiving large numbers of migrants. This combination of peripheral location and city size as factors in inducing migration from a different province provides an interesting contrast to the functions affecting migrants from the same province. It appears that, when moving to Ontario or Quebec from another province, migrants have a delicate trade-off to consider. They are likely to be moving from a rural area or a small- to medium-sized city. They may lack the social skills and/or the inclination to live in a metropolis, but the larger cities have better employment opportunities. Apparently the desire to be away from the metropolitan areas is, on balance, more important than the wish to be close to employment, since the coefficient of the urban hierarchy variable (measuring inaccessibility) is larger than the coefficient of the population size variable in the four functions in which they appear together, including the function for total migrants from a different province. The input data provide the best discrimination of all for migrants from abroad, with functions for six of the eight disaggregated components and the function for total migrants from abroad being accepted as statistically significant. The provincial, cultural, and linguistic variables (OQ, CL) dominate in these discriminant functions, appearing in all seven, and receive the largest coefficient in six of the seven functions. Urban areas in Ontario with their dominant English language and cultural characteristics receive much larger numbers of migrants from abroad than the urban areas in Quebec. Second in importance in six of the seven functions are the city size measures (MT, P2), with the larger metropolitan urban areas receiving the most migrants. Location variables (PR, UH) appear in four of the functions, indicating a possible preference for the central, more accessible urban areas. Economic variables appear in five of the functions, indicating a preference for administration and defence industries (+AD) over trade and commerce (-CM). Again the location variables provide a marked contrast with the two previous groups as described by location of origin, and this time with no ambiguity. A preference is expressed by migrants from abroad for the large, central, and easily accessible metropolitan areas. Like migrants from a different province,

Components of interurban migration streams

129

migrants from abroad appear to move as family groups, since the functions are fairly consistent over age groups and sexes. As before, urban areas with many opportunities for employment in services, particularly the administration and defence cities, attract the most migrants. Migrants from abroad, unlike domestic migrants, show no bias for or against manufacturing employment, but tend to avoid the urban areas specializing in trade and commerce. This may have been the result of a link between the language barrier confronting the new immigrant and the occupations found in those areas. Looking finally at the discriminant function for total inmigration, we see basic similarities and an intriguing difference with the functions for the disaggregated components of the migration stream. As before, the economic function variables are included, indicating a preference, regardless of age, sex, or location of origin of the migrant, for employment in services as opposed to manufacturing. Englishspeaking areas and areas of rapid growth are linked to high in-migration. The most surprising result for total inmigrants is the marked absence of location or city-size variables. This result, coupled with the previous results for the origin groups, suggests that an urban area's size and location determines where its migrants originate but not its total level of in-migration. From the above results one may hypothesize a filtering mechanism operating with regard to the locational decisions of migrants. Migrants from abroad, when moving to the Central Canada urban system, tend to gravitate towards the central cities with their cosmopolitan character, high employment opportunities and presumably less expensive, often shared, housing. Here the international migrant finds his fellow countrymen attempting to preserve the culture of the homeland, and his transition to Canadian society can take place gradually, minimizing the effects of culture shock. Migrants from a different province, moving fairly long distances within Canada, perhaps even the migrants from abroad of an earlier period, appear to prefer both the large urban areas and the peripheral urban areas. Migrants from the same province, moving short distances within the urban system, and possibly, the migrants from abroad or from a different province at an earlier period, prefer to migrate to peripheral independent centres and smaller cities. The longer the distance the migrants have to travel, the greater the cultural difference between their origin and their

130

Urban futures for Central Canada

destination, and the more they tend to gravitate towards the larger metropolitan centres and their satellites along the urban corridor. It may prove instructive to project the trends revealed by the discriminant analysis into the future, and to look at the patterns of population distribution which we may expect if the present trends continue. Of course it is unreasonable to assume that the exact values of the coefficients, or even their order of importance within the discriminant functions, will remain unchanged; but it does not stretch the credibility of the analysis too far to assume that the type of variables which currently affect in-migrationf and the direction of their effect, will remain essentially the same. It has been shown that economic function has played an important role in attracting migrants. We can expect that the shift in employment from manufacturing to service industries will continue. Urban areas whose economic base is dominated by manufacturing firms will experience a decline in growth rates relative to the rest of the urban system. Even if they were to lose very little of their population through out-migration, they will not receive the large numbers of in-migrants which accrue to urban areas with ample opportunities for employment in the service industries. If the provincial or federal governments decide to encourage the growth of particular urban areas or to construct new towns, they must ensure that service industries are encouraged to locate in such areas. We have also seen that the cultural and linguistic contrasts between the two provinces in the Central Canada urban system strongly modify the locational decisions of migrants. Urban areas in Ontario begin with a decided advantage in their ability to attract migrants relative to the urban areas of Quebec. In the future, unless countervailing public policy measures are applied, Quebec cities will experience population growth little greater than their rates of natural increase. The location and size of urban areas have little effect on the rates of total in-migration, but these characteristics exhibit marked differential effects on the rates of migration from different origins. If the filtering mechanism postulated above continues to determine the locational decisions of migrants from different origin groups, we can expect to find populations of markedly different character as we move from the metropolitan areas of the urban corridor to the remote, peripheral urban areas. Large central metropolitan areas

Components of interurban migration streams

131

like Toronto and Montreal will receive large numbers of international migrants, and one of their most distinctive characteristics will be ethnic diversity. It is difficult to predict where the migrants from a different province will locate, since the results for this component of the migration stream are so ambiguous, but they will probably be scattered throughout the urban system. Peripheral urban centres will be the most homogeneous in character, receiving large numbers of migrants from the same province. However with time this homogeneity will decrease, as the migrants from abroad and the migrants from a different province today become the migrants from the same province tomorrow. REFERENCES Barber, G. 1972. 'Growth Determinants in the Central Canada Urban System,1 in L.S. Bourne and R.D. MacKinnon, eds, Urban Systems Development in Central Canada: Selected Papers. Toronto: University of Toronto Press Britton, J.N.H. 1972. 'Economic Structure of OntarioQuebec Cities: An Occupational Analysis,1 in L.S. Bourne and R.D. MacKinnon, eds, Urban Systems Development in Central Canada: Selected Papers. Toronto: University of Toronto Press Bunting, T. 1972. 'Dimensions and Groupings in the OntarioQuebec Urban System, 1951 and 1961,' in L.S. Bourne and R.D. MacKinnon, eds, Urban Systems Development in Central Canada: Selected Papers. Toronto: University of Toronto Press Courchene, T. 1970. 'Interprovincial Migration and Economic Adjustment,1 Canadian Journal of Economics, 3/4: 550-94 Dominion Bureau of Statistics. 1962. 1961 Census of Canada. Bulletin 1.1-6: Population, Incorporated Cities, Towns and Villages. Ottawa: Queen's Printer Dominion Bureau of Statistics. 1969. 1961 Census of Canada. Bulletin SX-15: Population Sample, Characteristics of Migrant and Non Migrant Population, Metropolitan Areas. Ottawa: Queen's Printer Golant, S. 1972. 'Growth Characteristics of the OntarioQuebec Urban System,1 in L.S. Bourne and R.D. MacKinnon, eds, Urban Systems Development in Central Canada: Selected Papers. Toronto: University of Toronto Press Hill, F.I. 1972. 'Migration in the Toronto-Centred Region,' in L.S. Bourne and R.D. MacKinnon, eds, Urban Systems

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Development in Central Canada: Selected Papers. Toronto: University of Toronto Press Lowry, I.A. 1966. Migration and Metropolitan Growth: Two Analytical Models. San Francisco: Chandler Simmons, J.W. 1973. 'Net Migration Within Metropolitan Toronto,1 in L.S. Bourne, R.D. MacKinnon, and J.W. Simmons, eds, The Form of Cities in Central Canada: Selected Papers. Toronto: University of Toronto Press

7 Future mterurban transportation in Central Canada ROSS D. MACKINNON Central Canada has a highly developed multimodal transportation system. The highway system carries the vast majority of passenger traffic, although it is supplemented by effective air, rail, and bus services between many cities. The St Lawrence Seaway-Great Lakes waterway system and the railways and pipelines carry most of the commodity tonnage, although truck transport is also very important.1 These modes, together with the communications networks, link the set of cities and rural areas of Central Canada into a highly integrated system. Similar links connect the region to the larger system of Canada, the United States, and the rest of the world. Changes in the urban system can influence critically the appropriate form of transportation developments. Correspondingly changes in transportation can affect the manner in which the region behaves as a system. An attempt is made here to speculate about the probable two-way interactions between transportation on the one hand and the urban system of which it is a part on the other. The intention is to provide some general notions about the nature of transportation problems at the regional scale of analysis, the options available to the transportation decision-maker, their likely impacts, and which alternatives appear to be more likely than others to be adopted.

Interurban transportation

133

CHANGES IN THE NATURE OF TRANSPORTATION DEMANDS The demand for movement is virtually always a derived demand: the desire to transport oneself or one's commodities is derived from the need to have them in another location - a location which is more useful or beneficial than the present one. Thus the demand for transportation depends on the distribution of population and economic activity on the one hand, and the desired levels of social interaction and economic production on the other hand. Part I outlined alternative populations for the urban centres of Central Canada. The introduction of new services and the phasing out of old ones is obviously dependent on the spatial distribution of population among urban centres. Hamilton's forecasted population for 2001 varies from 800,000 to 1,400,000. If the latter rather than the former is realized, it is far more likely that a high-speed public transportation link would be built between Hamilton and Toronto. Differential urban growth is one of the important factors to bear in mind when considering the likelihood of alternative transportation systems. A special case is the introduction of a 'new town1 in the region, which would presumably be linked to the rest of the system by effective transportation services. Of course, as is discussed more thoroughly in the intraurban context (paper 13), such developments may have effects other than the ones anticipated. One of the most striking impacts of the introduction of the modern automobile-highway system has been the stagnation and decline of the small rural service centres. Increases in accessibility do not invariably mean increases in growth rates. Longer trips are possible, and in general the larger and more varied centres grow at the expense of smaller ones. Isolation often gives protection from competing centres. Projected increases in income levels and available leisure time will certainly have consequences on passenger transportation. One can expect a continued increase in airline traffic (in Canada air traffic has been doubling every five years) and recreational trips. In the latter context the works of Hodge (paper 12), Wolfe (1965), and Found and Morley (1972) illustrate the growing importance of multiplehome families. The resulting extension of the urban region creates problems of traffic congestion on a twice-weekly basis not unlike the diurnal movement of people in the conventional city. The physical manifestation of this type of

134

Urban futures for Central Canada

transportation demand is exemplified by the Laurentian and Eastern township autoroutes in Quebec and Highway 400 in Ontario. In most circumstances such routes are used for purposes other than their primary justification. Without controls they encourage the further spatial spread of Montreal and Toronto and diminish the economic importance of smaller distant centres (or at least change the economic character of such cities). Such transportation developments not only service actual and expected demands; they also encourage the growth of these and other demands. When a freeway is built to the east of Lake Simcoe, commercial and private recreational developments will accelerate, in all likelihood more than fulfilling the original demand projections. Any number of factors can change the nature of travel demands. Among them, perhaps one of the most interesting and unpredictable within the Canadian context would be the effects of the partial secession of Quebec. Undoubtedly a major reorganization of the transportation would be considered necessary: Toronto would become the major overseas airport; the port of Montreal would decline in importance; the relative amount of traffic (of both people and commodities) between Ontario and Quebec would probably decline substantially. Although the Canada-Quebec border would be highly permeable, both social and economic ties would be less important than they are now. Less dramatic factors than political fragmentation could markedly change the nature of transportation demands. As the structure of the economy changes either through new technologies or changing social priorities, the economic mix in urban areas and the demands for interaction between them will be altered. In the nineteenth century primary industries dominated the economy and, as a consequence, the transportation system. In terms of gross tonnage this is still the case in Canada. But in southern Ontario and Quebec the most important commodity flows, economically speaking, are the products of the highly integrated complex of secondary industry. One of the implications of this shift from primary to secondary industry is that transportation now comprises a much smaller percentage of value added into the production process than it once did. Modern industry is much less sensitive to transportation costs than it once was, and, since Central Canada is already well served by transportation facilities, it is much more difficult for new transportation developments to have a large impact on

Interurban transportation

135

the redistribution of population and economic activity. At the intercity level it is more likely that changes in the economy will require major adjustments to transportation services than the reverse. POTENTIAL CHANGES IN THE TYPE AND LOCATION OF TRANSPORTATION FACILITIES Published sources indicate the major planned additions to the freeway system of southern Ontario and Quebec: the completion of the Trans-Quebec highway from the Lac St Jean area to the US border via Trois Rivieres and the Eastern townships; completion of the North Shore freeway to Quebec City; completion of the Ottawa-Montreal link via a route somewhat to the south of the Ottawa River; a link west and north of Ottawa to North Bay; construction of a freeway extending from the Don Valley Parkway in Toronto north to the east of Lake Simcoe; a route joining London to Sarnia; completion of a multilane link from Orillia to North Bay; a freeway link connecting Highway 401 at Brockville to Ottawa. Some of these additions are more than warranted by their current traffic. Others are 'needed1 for more political purposes - to link together the major elements of the urban system and to 'show the provincial flag1 in areas which do not have major highway facilities. In recent years there has been considerable interest in developing more effective intercity transportation services in the Windsor-Quebec City corridor (Canadian Transport Commission/ 1970). The problem of serving this linear system of cities has by no means reached the near crisis proportions of the Boston-Washington region in the United States. Indeed, from the passenger's point-of-view, the current system appears to be working very well. Air, auto, and rail transport between Montreal and Toronto in particular is quite effective. In spite of this the federal government shows some interest in anticipating problems and improving service by experimenting with high-speed rail service and short-takeoff-and-landing (STOL) aircraft. Both these modes of transportation are designed to provide fast city-centre-to-citycentre service by sacrificing some of the trunk-line speed of conventional aircraft for shorter station-to-destination distances. A STOL service demonstration project is planned shortly. If successful, it will likely be expanded to serve Toronto within five years, and later London, Windsor, Quebec

136

Urban futures for Central Canada

City, and Sudbury-North Bay. These air services would supplement the major domestic and foreign routes which are strongly focused on Montreal and Toronto, each of which will have large new airports in the near future. The Transport Development Agency (TDA) is sponsoring research on guided ground transport.2 A permanent high-speed but fairly conventional transit service between Montreal and Toronto will be introduced shortly, eventually reducing travel times to about three hours. Preliminary studies would seem to indicate that more radical innovations, Tracked Air Cushioned Vehicles for example, will not be economically competitive in the foreseeable future (Clark, 1971). In terms of commodity flows the most dramatic development in the last ten years has been the introduction and proliferation of containerization. For many years technological developments have been primarily concerned with reducing line-haul times and costs. All too often savings in linehaul times and costs have been consumed by increases in terminal handling times and costs.3 Containerization has the advantage that large containers are easier to load, unload, and transfer to and from ships, trains, trucks, and aircraft than small boxes and cartons of different shapes and sizes. Container ports require a large investment to be effective i.e., economies of scale are extremely important, implying a small number of such ports in eastern Canada. The size and location of these ports are critical since the multiplier effects in terms of economic activity and employment of such an installation will be considerable. Not surprisingly, it appears that Montreal, Quebec City, Saint John, and Halifax will be the major container ports for eastern Canada. Of these certainly Montreal will continue to dominate, unless the political or labour situation makes this location less attractive. Inland ports such as Toronto will continue to decline in general cargo shipments as multimodal shipments become less costly and as container ships become too large for the St Lawrence Seaway (Canadian Transport Commission, 1972) . Similarly, container terminals for rail, truck, and air will become important. These attempts at intermodal coordination, strongly supported by the Canadian Transport Commission, by their very nature focus transportation and concomitant economic activity into a few locations. Such developments will further concentrate economic activity and, without offsetting controls and subsidies, bypass cities

Interurban transportation

137

with no such facilities. Location decisions regarding these facilities could be a powerful tool of regional development. As is the case with most such tools, however, very strong forces of economic inertia or external economies push them toward centres such as Montreal and Toronto. The stated desires of some politicians and planners to retard the growth of these cen.tres are frequently overriden by the agglomeration economies of large city locations. SUMMARY AND CONCLUSIONS This brief paper has speculated about the likely form of future interurban transportation in Central Canada. In summary: 1 Much more attention will be paid to increasing the effectiveness of the 'urban1 portion of the interurban trip. For example, less attention will be paid to line-haul travel times, as terminal-to-destination times become a higher percentage of the total trip. Two transportation options are available: one may attempt to reduce terminalto-destination distances (STOL, high-speed ground transport) or, alternatively, reduce station-to-destination access times by high-speed transit facilities. A third non-transportation adjustment is really a special case of the first - relocate the destination to sites near the terminal (e.g., airport hotels and conference centres). The other major example of this emphasis on the beginnings and ends of the transport process is the concern with terminal handling and containerization for all modes. This development will undoubtedly increase the effectiveness of the entire transportation process, but it inevitably focuses activity on the few cities lucky enough to be selected as container centres. 2 It is unlikely that radically different modes of intercity transportation will be introduced in Canada over the next twenty years. We can make such a forecast for several reasons. The region appears to be quite well served at present, and, even with continued rapid growth, the region will not be excessively congested. There appear to be far more pressing demands for government expenditures even within the transportation field intraurban tran§portation would seem to warrant more attention. 3 However one might expect an evolving modal split. In recent years the proportion of commodity flow carried by

138

Urban futures for Central Canada

pipelines and aircraft has increased markedly. In both cases this trend should continue. Pipelines, while they are quite restrictive in terms of the nature of the commodities they can carry, are an extremely effective mode of transportation. Transporting solids in suspension will become more important during the last quarter of this century. Aircraft can carry only commodities with a high value per unit weight,4 but such commodities are growing in importance relative to other types; in addition the development of larger aircraft and more efficient terminal-handling facilities will further encourage the growth of this traffic. Wallace (1971) estimates a 16fold increase in air cargo's share of the total ton-mile market from 1967 to 1987. It is estimated by 1980 that revenue from air cargo will exceed those from passengers in the United States. Of course as a percentage of total movements by weight it will continue to be quite small (0.80 per cent by Wallace's estimate), but its growth may be significant enough to attract some types of industries to locations near the major international airports. Lithwick (1970) speculates that the growth of air passenger mileage will shortly slow down and reach saturation level. With increases in incomes and leisure times and decreases in seat-mile costs as aircraft size increases, it is difficult to justify such a claim. Systems Research Group (1971) would seem to support this latter view, although on the basis of recent trends the rate of growth may slacken, particularly if energy costs increase rapidly. 4 Changes in available modes of transport will occur, but these will be more an evolution of existing modes rather than radically different ones. The passenger train will undoubtedly be upgraded, and service between major urban areas improved. For the foreseeable future improvements in the automobile will concentrate on safety and pollution rather than performance characteristics. Travel times will remain about the same, while capital and operating costs will increase. The automobile, while still by far the dominant mode of intercity passenger transportation, will probably decline relative to other modes at least between major urban centres. 5 Perhaps just as important as any hardware developments will be the increased emphasis on new information and control subsystems. Much of the problem of modern transportation systems is related to underutilization - vehicle

Interurban transportation

139

capacity being unused because it is not at the right place at the right time. Just knowing the location and status of railway cars, for example/ will help the system operate much more effectively. Of course the other aspect of underutilization derives from the extreme temporal and spatial peaking of flows in the system. By using innovative pricing and regulatory structures it is possible for the transportation system to be used more intensively and effectively. The airlines and railways already have introduced such practices (youth, excursion, and off-season fares, etc.) in an attempt to smooth out the peaks and increase total revenues. One should expect an increase in these 'software' innovations as aircraft, trucks, ships, and railway cars become larger. In summary, then, we should expect a slowly evolving interurban transportation system with an increasing emphasis on terminal handling and access, safety, pollution, energy consumption, and reliability, rather than line-haul speed. It will be possible to cope with the anticipated growth in passenger and commodity flows over the next thirty years with quite conventional modifications. NOTES 1

2

3

4

For Canada as a whole ton-mile percentages in 1968 were as follows: rail, 42 per cent; pipeline 25 per cent; water 24 per cent; truck 9 per cent; air, less than 1 per cent. Data were assembled and reported in Wallace (1971). See McLaren and Myers (1971); also an Institute of Guided Ground Transport has been set up at Queen's University, sponsored by TDA and the two national railways. Moore and Pomrehn (1971) claim that for a shipment from an inland US point to an inland European point no less than 54 per cent of the total shipping costs are accounted for by stevedoring! For example, in 1967, 0.1 per cent of the total weight of US foreign trade was shipped by air, although this represented 12.5 per cent of the value of such trade (Moore and Pomrehn, 1971).

REFERENCES Canadian Transport Commission. Transport Study. Ottawa

1970.

Intercity Passenger

140

Urban futures for Central Canada

Canadian Transport Commission. 1972. Research Base for Development of a National Container Policy: Phase II. 3 vols. Ottawa Clark, G.A. 1971. Comparison of Strategies for Development of Intercity Transport. Ottawa: Canadian Transport Commission Research Publication 16 Found, W.C., and Morley, C.D. 1972. A Conceptual Approach to Rural Land Use - Transportation Modelling in the Toronto Region. Toronto: University of Toronto-York University Joint Program in Transportation. Research Report 8 Lithwick, H. 1970. Urban Canada: Problems and Prospects. Ottawa: Central Mortgage and Housing Corporation McLaren, W.S. , and B.B. Myers. 1971. Guided Ground Transportation Study. Prepared for Transport Development Agency by Canadair Ltd, Montreal Moore, C.G., and Pomrehn, H.P. 1971. 'Technological Forecast of Marine Transportation Systems,1 Technological Forecasting and Social Change, 3: 99-135 Shaw, M.F., and Culley, E.K. 1972. Urban Access in the Canadian Corridor. Ottawa: Canadian Transport Commission Research Publication 32 Soberman, R.M., Clark, G.A., and Parkinson, T.E. 1971. Evaluation of New Technology for Intercity Travel. Ottawa: Canadian Transport Commission, Research Publication 29 Wallace, R.S. 1971. A Domestic Multi-Model Goods Distribution Model with Emphasis on Air Cargo. The Transport Group, Department of Civil Engineering, University of Waterloo, Waterloo, Ontario Wolfe, R.I. 1965. Parameters of Recreational Travel in Ontario: A Progress Report. Department of Highways of Ontario Report No. RB111, Downsview, Ontario

8 Intercity linkage patterns JAMES W. SIMMONS and IAN J. LINDSAY Inherent in the notion of an urban system is a focus on the linkages among cities and their role in the evolution of urbar structural characteristics. This paper examines the relation-

Intercity linkage patterns

141

ship between spatial interaction, measured by telephone calls among the cities of Central Canada, and various structural characteristics of the centres/ such as demographic, social, economic, and housing variables. It complements earlier analyses of the urban system of Ontario and Quebec, which have concentrated on structural characteristics (see Bunting, 1972; Golant, 1972; and Barber, 1972), and extends the work by Simmons (1972) on telephone calls and other forms of interaction. In a final section the implications of urban growth and future linkage patterns are briefly explored. Two main themes underly this discussion. First, it is assumed that some insight into future linkage patterns is a significant component of the urban future. Second, it is suggested that the pattern of linkages observed at present and projected in the future will affect those future growth patterns which are sensitive to accessibility to the rest of the urban system. CURRENT PATTERNS OF ACCESSIBILITY The data Data on long-distance telephone calls (both business and residential) for an average day in 1967 were obtained from Bell Canada (Simmons, 1972).! The 61 Ontario-Quebec toll centres which are enumerated correspond for the most part with the 'census metropolitan areas,1 'major urban areas,1 or 'other urban centres,' but in some cases (e.g., Beaverton) the name of the particular urban agglomeration refers to a large, functional region which has no census counterpart (table 8.1). The centres are defined according to the particular needs of Bell Canada (Goulden, 1968). Structural variables for the first three types of toll centres were obtained from the 1961 and 1966 Censuses. For the other centres socioeconomic, demographic, and other variables were estimated as the urban proportions of the county or counties corresponding to the area of the toll centre. In addition to this estimation procedure, there are other possible sources of error. Small centres at the borders of regions may be closer to each other than to other parts of their respective toll areas. The system definition makes Quebec City appear relatively isolated because centres to the north and east have been excluded; similarly Windsor is cut off from the substantial cross-border contact with Detroit.

142 Urban futures for Central Canada TABLE 8.1 Ontario-Quebec telephone toll centres

Toll centre

Definition

1961 population

1 Toronto 2 Brampton 3 Fort Erie 4 Windsor 5 Barrie 6 St Thomas 7 Woodstock 8 London 9 Stratford 10 Hamilton 11 Orangeville 12 Peterborough 13 Simcoe 14 Beaverton 15 Bracebridge 16 Brantford 17 Chatham 18 Clinton 19 Huntsville 20 Kitchener 21 Lindsay 22 Midland 23 Newmarket 24 Niagara Falls 25 Orillia 26 Oshawa 27 Owen Sound 28 Parry Sound 29 Guelph 30 Port Hope 31 St Catharines 32 Sarnia 33 Tillsonburg 34 Walkerton 35 We Hand 36 Montreal 37 Trois Rivieres 38 Kingston 39 Thetford Mines 40 Victoriaville 41 Drummondville 42 St Jerome 43 Smiths Falls

1 3 4 1 3 3 3 1 3 1 4 2 4 4 4 2 3 4 4 1 3 4 4 2 3 2 3 4 2 4 2 2 4 4 3 1 2 2 3 3 2 3 4

1,824,481 18,467 74,013 193,365 21,169 22,469 20,486 181,283 20,467 395,189 16,095 49,902 50,475 40,292 26,705 56,741 29,826 53,805 26,705 154,864 11,399 125,926 57,951 54,649 15,345 80,918 17,421 29,632 41,767 39,916 95,577 61,293 50,013 43,036 36,079 2,109,509 83,659 63,419 21,618 18,720 39,307 24,546 40,313

2001 population (estimated) 6,000,000 200,000 88,000 400,000 75,000 40,000 95,000 450,000 30,000 900,000 26,000 100,000 76,000 53,000 28,000 100,000 70,000 54,000 28,000 450,000 25,000 201,000 99,000 91,000 25,000 270,000 25,000 28,000 100,000 30,000 250,000 140,000 52,000 43,000 150,000 5,500,000 150,000 125,000 50,000 50,000 60,000 80,000 41,000

Intercity linkage patterns

143

Table 8.1 continued

Toll centre

Definition

44 St Hyacinthe 45 Joliette 46 St Agathe 47 St Jean 48 Granby 49 Cornwall 50 Valleyfield 51 Belleville 52 Shawinigan 53 Hawkesbury 54 Renfrew 55 Sorel 56 Sherbrooke 57 Quebec 58 Pembroke 59 Brockville 60 Ottawa 61 Lac Megantic

3 3 4 2 3 3 2 3 2 4 4 3 2 1 3 3 1 4

1961 population

22,354 18,088 65,958 34,576 31,463 43,639 29,849 30,655 63,518 27,226 72,844 17,147 70,253 357,568 16,791 17,744 429,750 30,600

2001 population (estimated)

50,000 50,000 74,000 75,000 50,000 100,000 60,000 80,000 75,000 27,000 73,000 50,000 150,000 800,000 30,000 40,000 1,000,000 29,000

1 Defined as: (1) census metropolitan area;(2) major urban area; (3) other urban centre; (4) 'county surrogate'

Calls within a toll area are excluded. Both residentialand business-originated calls were analyzed, and, while the proportion of residential phones per toll centre is fairly constant (67 per cent to 79 per cent), the variation in long distance calls made is much greater (28 per cent to 62 per cent). Models of call generation The first phase of the analysis is a series of regression models which attempts to predict the inflow and outflow of long-distance residential and business calls to a centre. The selection of independent variables draws on several sources: insights about the characteristics of the urban system from other studies (Bunting, 1972), from the previous descriptive materials on the long-distance telephone pattern (Simmons, 1972), and from the constraints imposed by census materials.

TABLE 8.2 Correlation matrix for telephone call generation, Central Canada toll centres No. Name of variable 1 2 3 4 5 6 7 8 9 10 11 12 13 14

% age greater than 65 % French mother tongue % managerial occupations % single- detached housing Logio average mean first passage time Logio residential phones LogiQ business phones Log iQ all phones Logio residential outcalls Logio residential incalls Logio business out-calls LogiQ business in-calls Logio total out-calls Logio total in-calls

n = 61

1

1.0000

2

3

4

-0.6788 1.0000

0. 3809 -0.3641 1.0000

0.6104 -0 .8245 0.2639 1.0000

6

7

8

0.1434 0.0478 0.0220 0.3464

-0.3198 0.0162 0.0430 -0.3848

-0 .3439 0.0731 0.0492 -0 .4281

-0.3273 0.0318 0.0450 -0.3970

1.0000

-0.7174 1.0000

-0 .6855 0.9905 1.0000

-0.7096 0.9993 0.9949 1.0000

5

-0.2685

-0.0539

0.0467

-0 .3065

-0.7857

0.9187

0.8861

0.9116

0.2313 -0.2268 -0.2410 -0.2481 -0.2388

-0.0286 -0.0594 -0.0512 -0.0580 -0.0407

0.0581 0.0689 0.0500 0.0533 0.0537

-0 .3403 -0 .3292 -0 .3341 -0 .3224 -0 .3391

-0.8104 -0.7750 -0.7958 -0.7881 -0.8058

0.9164 0.9657 0.9588 0.9549 0.9465

0.8934 0.9546 0.9428 0.9339 0.9274

0.9118 0.9642 0.9561 0.9510 0.9630

Intercity linkage patterns

145

After a great deal of experimentation and elimination (based on redundancy with respect to other predictors/ and weakness of relationship with the dependent variables), the variables described in table 8.2 remain: measures of demographic structure, ethnicity and social class, along with a housing measure that captures part of each of the other three social dimensions. Average mean first passage time (AMFPT) is a measure combining size of place and centrality to the rest of the system. The other scale measure is the number of telephones, by type, in each toll centre in 1967. Since the distribution of toll centre sizes is approximately log normal, the scale measures were converted to logarithms. The results are very simple and quite powerful (table 8.3). For each of the six dependent variables (residential calls in and out, business calls in and out, and all calls in and out), two independent variables predicted over 95 per cent of the variation in the calls made. The consistently most powerful variable was average mean first passage time (AMFPT) - the measure itself derived from the telephone call matrix, which reflects access to nearby centres, and hence propensity to call or be called. If the call generation measures included calls to all centres instead of just to those in the system, the utility of AMFPT would decrease. The number of telephones in each case added some further explanation. Most notable was the absence of any social characteristics of cities in modifying the number of incalls or outcalls (except as this effect is also contained within the variable AMFPT). Of some interest are the variations in the regression coefficients. The residential calls are negatively related to AMFPT because, as toll centres become larger, more calls are placed internally and the proportion of long-distance calls declines. At the same time larger higher-order central places have a greater propensity to initiate calls and receive business calls, overcoming the internalization effect. Models of flow dyads A simple gravity model has been developed to predict residential and business calls between toll centres:

146

Urban futures for Central Canada

where Wj_, Wj, X^r Xj represent various structural characteristics of the origins and destinations. Distance is measured TABLE 8.3 Telephone call generation:

Regression coefficient

Independent variables

Dependent variable:

t statistic

3 coefficient

L

°910 residential out-calls

Log residential phones Log^J AMFPT R2 = 0.9532 R = 0.9763

Regression results

-0.0585 -1.0914

-0.7655 -11.6312***

-0.0685 -1.0410

F = 590.3223 a = 5.5585

Dependent variable: Log residential in-calls Log10 residential phones Log 10 AMFPT R2 = 0.9881 R = 0.9941

Log10 business phones Log:"" AMFPT

-0.2339 -1.2130

Log

10 business out-calls 0.2601 -0.7298

5.6282*** -12.1302***

0.3178 -0.6849

F = 1125.8518** a = 3.7135

Dependent variable: Log business phones Log^ AMFPT R2 = 0.9942 R = 0.9971

-5.1929*** -26.9355***

F = 2417.2021** a = 6.3169

Dependent variable:

R2 = 0.9749 R = 0.9874

-0.1849 -1.1784

Log 10 business in-calls 0.0999 -0.9237

F = 4970.9453** a = 7440

LEVEL OF SIGNIFICANCE ***0.001 **0.01 *0.05

4.5666*** -32.4583***

0.1239 -0.8808

Intercity linkage patterns

147

as airline distance between centres. The number of residential or business telephones is used instead of population. AMFPT is again employed as an accessibility index, and the same group of socioeconomic, housing, and demographic variables employed in the call-generation model are again included (see table 8.4). The results (table 8.5) are summarized as follows: 1 The simple gravity model (ignoring possible biases, such as spatial autocorrelation and other possible violations of assumptions required for rigorous regression analysis) largely accounted for the variation in the dependent variables, telephone interaction. An R% value of 0.78 is obtained for residential calls and 0.79 for business calls. The accessibility measure is much less important than either number of telephones or distance. 2 The socioeconomic, demographic, and housing variables are largely irrelevant. Even French mother tongue (as postulated by MacKay, 1958) contributes only slightly to an explanation of telephone interaction, and then the signs are in opposite directions for residential and business calls. Part of the difficulty is the result of a high correlation of this variable with distance (0.68) in this spatial system (table 8.4). Managerial occupations, single-detached housing, and age greater than 65 are also redundant as independent variables. Accordingly the irrelevant variables have been excluded, and residential and business interaction are predicted as a function of number of telephones and distance. 3 The structure of the models is remarkably similar for both residential and business interaction. AMFPT has the same influence and in both cases is much less important than the telephone and distance variables. The distance exponent is slightly smaller for residential calls (-1.3979) than business calls (-1.4409) implying that residential telephone interaction is more spatially extensive than business calls. Business calls, on the other hand, are more responsive to differences in the size of centre. Some insight into the reliability of the gravity model coefficients can be obtained, using the approach developed by Curry (1970). He distinguishes between a 'map effect,' spatial interaction reflecting the distribution of centres of various sizes, and a 'distance effect,' a result of the friction of distance resulting from increased costs of longer calls and reduced number of opportunities. The diffi-

TABLE 8.4

Correlation matrix of gravity model variables N o . Name o f variable

1

2

3

4

5

6 7

8 9

1 0

1 Residential phone calls 1.0000 0.9622 -0.6611 -0.1015 -0.2657 2 Business phone calls 1.0000 -0.6198 -0.1210 -0.2590 3 Distance 1.0000 0.0293 0.2708 4 (% managerial occupations:* - % MOj-) 1.0000 0.0555 5 (% age greater than 65i - AGEj) 1.0000 6 (% French mother tonguei - % FMTj) 7 (% single-detached housing.^ - % SHj) 8 (Residential phonesi x RPj) 9 (Business phones^ x BPj) 10 (Average mean first passage timei x AMFPTj n = 3660 1

All variables are in log1Q form.

-0.4149 -0.2681 0.5581 -0.3859 -0.2452 0.6051 0.6823 0.4367 0.0195

0.5487 -0.5565 0.5993 -0.5952 0.0430 0.1123

-0.1890

0.0539 -0.1543 -0.1421

0.1422

0.2812

0.1860 -0.1716 -0.1664

0.1492

1.0000

0.4982

0.0657

0.1002

0.0159

1.0000

0.0761

0.0911 -0.0330

1.0000

0.9898 -0.9200 1.0000 -0.9027 1.0000

Intercity linkage patterns TABLE 8.5 The gravity models

__

_ _ Independent variables Dependent variable: Log10 Log10 Log1() Log1() Log1Q LogiQ LogiQ R R

Regression coefficient

= 0.7793 = 0.8828

R R L g

= 0.7903 = 0.8890

0.4412

-64.4547*** 1.1668 3.8139*** 2.0542* -2.7829** 41.6309*** 15.7606***

-0.7297 0.0092 0.0320 0.0232 -0.0254 0.8875 0.3346

-93.2849*** 76.9013***

-0.6956 0.5734

Log^ business calls ij -1.5186 -0.0267 0.0667 -0.0149 -0.0288 0.9877 0.3980

-61.9403*** -2.0900* 4.9651*** -1.6333 -2.1926* 46.5153*** 14.6676***

-0.6789 -0.0161 0.0406 -0.0180 -0.0195 0.8877 0.2782

-91.0152*** 86.8503***

-0.6639 0.6335

F = 7387.2500** a = -0.4899

° iO distance ij LogiQ (BP.£ x BPj) R R

0>9621

-1.3979 0.6059

distance ij (% MO^ - % MO-) (% AGE i "% AGE 0 (% FMTj; - % FMT^) (%SHi - % SHO J (BPi X BP J'> (MFPTi x MFPTj)

= 0.8058 = 0.8977

-1.5046 0.0141 0.0484 0.0177 -0.0346

F = 1841.7832** a = -5.2165

Dependent variable: Log10 Loglo L g ° iO Loglo LogiQ L g ° iO LogiQ

— ————-————__ $ coefficient

F = 7170.6133** a = -0.6048

Loglo distance ±. Log1() (RP,. x pp^y R R

t statistic

Log^ residential calls ij

distance^(% MO.; - % MOj) (% AGEj; - % AGE,-) (% FMTj - % FMTj) (% SHi - % SHJ) (RPi x Rpj) (AMFPT^ x AMFPTj)

= 0.7968 = 0.8926

149

-1.4409 0.6840

F = 1966.6187** a = -4.2695

LEVEL OF SIGNIFICANCE ***0.001 **0.01 *0.05

150

Urban futures for Central Canada

culty in empirical analyses using the gravity model is that both these effects occur simultaneously, and cannot easily be separated. However the map effect can be equated with the spatial autocorrelation of opportunities, and, if the toll centres are not significantly spatially autocorrelated, then the distance coefficient does reasonably indicate the degree of spatial friction. A procedure similar to that employed by Hodgson (1972) is used to estimate the amount of spatial autocorrelation in the Ontario-Quebec system of toll centres. Essentially, for a particular variable the values occurring in the 61 toll centres are correlated with those occurring in the set of nearest neighbours. Since Curry (1970) suggests that spatial autocorrelation must be appreciated at several scales, this approach is followed for nearest neighbour intervals up to the ninth order. In addition nearest neighbour intervals are measured rather than uniform spatial differences. The degree of correlation of values at different intervals is generally low for the variables employed in the gravity model (table 8.6). Subject to the biases of this crude procedure, it appears that the spatial autocorrelation of opportunities is not a significant problem in the analysis of telephone linkages. TABLE 8.6 Spatial autocorrelation among interaction variables

Variable Residential phones Business phones All phones AMFPT

Order of nearest neighbour 1st 2nd 3rd 4th 5th

-0.05 -0.04 -0.01 -0.08 -0.05

6th

7th

8th

9th

0.01 -0.05 -0.05 -0.08

-0.06 -0.05 -0.03 -0.08 -0.06 -0.00 -0.05 -0.04 -0.07 -0.05 -0.04 -0.04 -0.08 -0.05 0.01 -0.05 -0.04 -0.08 0.53 0.29 0.20 0.13 0.07 -0.08 0.22 0.03 0.04

FUTURE PATTERNS

Extrapolations of population growth Given the models produced in the previous section, future linkage patterns can be forecast by using the future populations for urban centres presented in appendix B and summarized in paper 3. Median forecasts are selected for each

Intercity linkage patterns

151

toll centre included in the population forecast section. For the smaller toll centres a cruder procedure is employed. Growth is estimated either as a 50 per cent increase over the 1966 population, or the area is estimated not to grow at all (see table 8.1). The following gravity models are estimated and used for the forecast:

Residential and business phones are estimated using the present telephone per capita ratios for each toll centre. Telephone use may be higher for the year 2001, but there is no reason to expect a spatial bias in this change. Using these equations residential and business interaction matrices for the toll areas (61 x 61) for the year 2001 are derived, and then examined using the same procedure as in Simmons (1972). The gross business calls and largest business calls from each centre are plotted in figures 8.1 and 8.2. The resulting maps are directly comparable to those presented previously for the present period (Simmons, 1972), but imply some significantly different relationships. The concentration of linkages along the Quebec-Windsor corridor is maintained, but the relative strength of flows along the urban corridor declines relative to calls to the two powerful urban fields of Montreal and Toronto. If these gross flow patterns are simplified into a hierarchical pattern by identifying the destination of the largest outflow from each toll centre, the implications are dramatic. Toronto and Montreal now dominate the entire system, with virtually no intermediary centres remaining. London, Kitchener, and even Ottawa appear to serve very few other centres. Other factors It appears that spatial distortions in the distribution of population growth alone are creating a restructuring of relationships in the urban system toward a stronger role for the two metropolitan poles, and correspondingly weaker

Figure 8*1

2001 business calls:

Gross flows (distance exponent b = 1.4409)

Figure 8.2

2001 business calls:

Largest outflows (b = 1.4409)

154

Urban futures for Central Canada

roles for the middle-order urban nodes. This tendency could be accelerated by changes in the regression parameters which also favour larger places, such as increases in the propensity to own telephones or to make calls as the size of the toll centre increases, or most likely, a relative decline in the strength of the distance exponent. If, as is expected, the distance-decay coefficient is reduced (e.g., to -1.00) the pattern shown in figure 8.3 for total flows would result. The most striking aspect of this latter hypothesis is a strengthening of contacts along the corridor among larger centres in the two metropolitan fields. However the role of secondary centres is further weakened. Similar patterns can be observed for residential telephone calls, although the hierarchical structure, particularly the role of middle-level centres, remains slightly more visible. Once again, though, the observed pattern is overwhelmingly dominated by the two metropolitan poles. Impact of future linkage patterns The patterns of linkage within the urban system forecast here may be of limited generality. They are defined by a single communication mode - one which is susceptible to technological and institutional changes, particularly those affecting rate structure. They are, moreover, based on a pattern of response to the existing urban hierarchy. Their behaviour with respect to the future urban structure cannot be anticipated with certainty. At the same time a previous study (Simmons, 1972) suggests that the pattern of business calls, in particular, confirms intuitive notions of the urban hierarchy in a very satisfying manner and appears to be a better indicator than any other available measure. The trends in interurban relationships suggested here, then, merit serious consideration. The major trend (figure 8.4) is the increased polarization of urban development within Central Canada. The size, the role, the future growth of all urban places will be increasingly determined by their relation to Toronto or Montreal. The relationships to other cities increasingly will be direct - without intermediary centres. Each centre will serve its own population and go to Toronto for higher-order facilities; the regional roles of centres such as London, Ottawa, and Quebec will decline. The strength of the corridor - vis a vis the two metro-

Figure 8.3 2001 business calls:

Gross flows «, = l.0000)

Figure 8,4

2001 business calls:

Largest outflows (b = 1.0000)

Intercity linkage patterns

157

politan poles - will depend on the ability to reduce further the friction (in time and money terms) of distance. As this friction declines contact between the members of the two poles (Toronto and Montreal) becomes significant. Conversely, as it increases the two poles are more isolated. It can be argued that the telephone linkages provide a good surrogate for the whole range of future contact patterns within the urban system, at least in qualitative terms. Ground transport is increasingly responsive to distance rather than network facilities, as the transportation net is extended and filled in. Air travel, on the other hand, accentuates the polarity by increasing the role of the two major metropolitan nodes. NOTE 1

We wish to thank Bell Canada for the use of these data.

REFERENCES Barber, G. 1972. 'Growth Determinants in the Central Canada Urban System,1 in L.S. Bourne and R.D. MacKinnon, eds Urban Systems Development in Central Canada: Selected Papers. Toronto: University of Toronto Press Bunting, T. 1972. 'Dimensions and Groupings in the OntarioQuebec Urban System, 1951 and 1961,' in L.S. Bourne and R.D. MacKinnon, eds, Urban Systems Development in Central Canada: Selected Papers. Toronto: University of Toronto Press Curry, L. 1970. 'Applicability of Space-Time Moving-Average Forecasting,' in P. Raggett, A. Frey, and M. Chisholm, eds, Regional Forecasting. London: Butterworth Golant, S. 1972. 'Regression Models of Urban Growth in Ontario and Quebec,' in L.S. Bourne and R.D. MacKinnon, eds, Urban Systems Development in Central Canada: Selected Papers. Toronto: University of Toronto Press Goulden, J.C. 1968. Monopoly. New York: Putnam Hodgson, J. 1972. 'Variability in the Growth of Small Urban Areas,' in L.S. Bourne and R.D. MacKinnon, eds, Urban Systems Development in Central Canada: Selected Papers. Toronto: University of Toronto Press MacKay, J.R. 1958. 'The Interactance Hypothesis and Boundaries in Canada: A Preliminary Study,' Canadian Geographer, 2: 1-8

158 Urban futures for Central Canada

9 Forecasting the regional economy of Ontario JOHN N.H. BRITTON and GERALD M. BARBER

This paper projects recent labour force trends for Ontario, disaggregated by both region and sector, to the year 2001. These projections are then evaluated in terms of possible planning developments by the provincial government. It is inevitable that studies of this kind contain apologetic notes about the logical bases of the results of this type of exercise. The general assumption of the continuity of present trends, in particular, is an admission of ignorance of the processes of long-run change in a regional economy. The use of this naive methodology, however, can be partially explained by the absence of a well-developed theory of regional economic change. In addition a more sophisticated projection of regional employment based on output and various productivity assumptions is virtually impossible because of insufficient information on regional differences in the various producing sectors. To forecast the economic geography of Ontario in the year 2001 requires estimates of the locational and sectoral distribution of the work force. It can be argued that the changes in the level of activity of individual sectors (i.e., employment and output) are a product of the economic system, whereas population and work force in general may be strongly influenced by demographic-sociological relationships. These two macroscopic views of human activity merge however; equality is established between the total labour force on one hand and unemployment and the aggregate level of activity (measured by employment) on the other. This is equivalent to assuming that the demand conditions determining employment in the long run determine the supply of the labour force. Provincial forecasts of employment by sector (obtained from Ontario government sources) are discussed in the first part of the paper. Labour force estimates may be obtained from demographic projections given assumed participation rates, and these are outlined in the second part of the text (see paper 4).

Forecasting Ontario's regional economy

159

Those two sets of projected 'control1 totals are used in deriving regional-sectoral projections; these normalized forecasts are discussed in part three. Finally the implications of the projected regional-sectoral labour force pattern are discussed in terms of provincial location policy. SECTORAL EMPLOYMENT PROJECTIONS FOR ONTARIO If the economic basis for employment is accepted, projection of sectors can be undertaken far more easily at the provincial level than at the regional level for several reasons. First, there are substantially greater data resources available at the provincial level (for example, reports from the Census of Manufactures and the Labour Force Survey). Second, the national data set can be used for Ontario, which comprises such a large part of the national totals of all activities. Third, past trends have been more regular for the province than for individual regions. In Ontario the former provincial Department of Treasury and Economics (DTE) has made projections for sectoral employment based on expected output levels which have been estimated on the basis of the information described above and an assumption about the level of the national growth rate. The output 'data1 are used in conjunction with productivity projections as the main ingredients of the provincial sectoral employment estimates. The complex basis of the growth of productivity needs to be tackled in making estimates for Ontario. However productivity change is essentially a long-term process and is, therefore, amenable to projection. Rather than exploring the anatomy of this forecasting procedure, the work reported here uses the forecasts developed by DTE. The projection technique used by DTE has produced essentially linear semilogarithmic trends for all sectors. The manufacturing trend is composed of many individual projections, and in a number of instances non-linear output patterns exist for disaggregated sectors. The establishment of output projections is relatively easy in manufacturing where considerable data may be derived from the Census of Manufacturers; it is much more difficult in the service sector of the economy where the level of activity can only be measured staisfactorily in terms of labour input rather than directly by output. Canadian 'output1 is considered to have increased at a faster rate than employment,

160

Urban futures for Central Canada

but the underestimate of output is inevitable: 'one is left with the impression that the total volume of output in the service sector has grown at roughly the same rate as that of the goods sector over the postwar period1 (Economic Council of Canada, 1968) - that is, not more rapidly as employment data suggest, and not more slowly as output data suggest. The significance of 'productivity1 increases in a consideration of structural change in the economy is paramount. In manufacturing substantial increases in productivity have occurred, and these are attributed to a number of influences including changes in characteristics of the average employed person in manufacturing, increases in capital per worker, the small proportion of female employment, and the substantial improvement in the educational level of workers. At the same time the most impressive improvements in labour productivity have occurred in agriculture, forestry, and fishing, where capital has been substituted for labour, in mining, which has become even more capital-intensive than previously, and in construction. Employment trends in the Ontario economy have been extended to 2001 (table 9.1): agriculture, for example, is exTABLE 9.1 Ontario employment projections, 1971-2001 1971 Agriculture Forestry and fishing Mining Manufacturing Construction Transportation and utilities Trade Finance, insurance and real estate Service Residual 1

132190

% 4.4

1981 93640

% 2 .4

1991 72250

% 1.4

20011 52620

% 0.7

13660 0.4 13210 0.3 14330 0.5 12650 0.2 24890 0.6 22070 0.4 28090 0.9 19550 0.3 859970 28 .5 1041880 26 .8 1279870 25 .0 1554380 22.5 189140 6.3 185030 4.8 188290 3 .7 185770 2.7 208640 6.9 487510 16 .2

228980 5.5 630160 16 .0

255300 5.0 281780 4.1 815100 15 .9 1053680 15.3

130610 4.3 178500 4.6 243900 4.7 333120 4.8 901950 29 .9 1403530 36 .1 2130500 41 .5 3280410 47.5 83200 2.1 107630 2 .1 135000 1.9 65000 2.1

Extrapolated from 1971-91 projections.

Forecasting Ontario's regional economy

161

pected to decline in employment at about the same rate as output will expand. Decline in the number of farms is longstanding, total land under cultivation has fallen, average farm size has increased, and large-scale commercial farms (specialized operators in the main) have appeared. These factors, in conjunction with the use of improved techniques and heavy applications of capital, have made recent changes possible and justify the projected provincial change in employment. In mining a boom in the late 1950s and early 1960s led to substantial new employment, but this sector is projected to decline, though less rapidly tuan agriculture; output is expected to rise more rapidly reflecting productivity gains that have been made in mining through a notable inflow of capital. The rate of employment decline in the forestry, fishing, and trapping sector has been more rapid in the past, but a substantial increase in output is expected to occur through productivity gains; while additional employment is anticipated, the gains in output will reflect more the increased application of capital, especially in operations concerned with pulpwood. The projections for manufacturing indicate substantial productivity gains. Since 1961 there has been a notable increase in the manufacture of durable goods exceeding the expansion of non-durable production. The increased activity in the auto industry is an important cause of this, and a continuing improvement in productivity levels for the whole sector is expected, though this is contingent on stability in marketing arrangements. There are various aspects to the debate over the significance of foreign ownership of a substantial share of Canada's industry for future manufacturing production and employment growth; for the most part, however, the structural and dynamic significance of foreign ownership has been poorly developed. But recently the Science Council of Canada (1971), questioning the extent to which sufficient new technological input is being made to manufacturing from Canadian sources, has pointed out the significance of the multinational firm to Canadian manufacturing research and development, and has emphasized the need for a Canadian science policy. Until recently a constant proportion of the Canadian labour force was employed in manufacturing. Many expected this trend to continue. In 1967, however, the share of the

162

Urban futures for Central Canada

labour force engaged in manufacturing began to decline, initiating a new trend. What has impressed the Science Council is that growth in service employment has been insufficient to take up the slack in the labour force.1 Over the past ten years most new employment in manufacturing has occurred in medium- and high-technology-using industries.2 Ontario's share of the six high-technology industries is now 62 per cent (1968) and their share of provincial employment is 43 per cent. The extreme sensitivity of jobs in these industries to general economic conditions is of considerable importance in the future of the manufacturing sector of the Ontario economy. It is maintained that productivity in Canadian manufacturing is significantly lower than that in the United States, and that there is a similar difference in the ratio of output/invested capital. These reflect, in turn, less specialization in Canadian plants, smaller markets, less efficient transfer of technology, and perhaps lower managerial quality. For the technology-based industries signs of poor economic health are made evident by the limited ability of this sector to reinvest because of declining profitability: the Canadian demand for these goods is increasingly being met by foreign suppliers; overseas markets for these goods are gradually being eroded. Are the recent trends part of a long-run scheme for the economy? Unless steps are taken, in the opinion of the Science Council, the employment estimates for Ontario to 2001 would have to be revised considerably! Better access to markets and capital, improved competitiveness and productivity, more effective managerial skills, better utilization of the work force and an improved capability to use new technology all seem pertinent. The construction sector, comprised of a number of components - residential, industrial, commercial, institutional and engineering - is considered to have changed the least of all sectors in terms of technology and building materials. But labour costs are expected to promote changes leading to a greater share of factory-built housing (the output of the construction industry is projected to double by 2001 without employment change). It should be noted, however, that the 1951-61 labour force data do not link well with estimates for construction, but this general problem seems to have been created by the fact that the employment projections have been based on data from the late 1950s, and have thus avoided estimation problems associated with the 1961 recession.

Forecasting Ontario's regional economy

163

Within the transportation and utilities sector two trends have been occurring and are projected to continue. Utilities are characterized by output expansion in response to changes in the demand level while employment is thought to be relatively stable. Transport storage and communication activities have an exceptional productivity record compared with the rest of the tertiary sector, and, while employment has apparently not risen appreciably, there has been high productivity growth which has been attributed to the large size of operating firms, their level of capitalization, and the advanced technology employed. The projected increase in employment compared with output, is rather modest as a result of these characteristics. By contrast the recently expanding employment in finance, insurance, and real estate (FIRE) is not matched by rising productivity; there are measurement problems, however, and larger firms with improved procedures could be expected to lead to greater- productivity. Employment and output projections for trade, community business and personal service, and public administration (a growth industry) do not indicate major changes occurring in productivity. THE CANADIAN PATTERN OF CHANGE Projections for Ontario gain significance when related to the overall pattern of change for the Canadian economy and when compared with projections made for the nation. Both in terms of production and employment the share of the Canadian economy devoted to secondary industry has remained stable over an 80-year period, replicating what has been observed in the United States and other developed economies. The increasing industrialization of Canada, however, is revealed by the decline in primary activities (particularly in agriculture) and the expansion in the share of the tertiary sector in national production and employment (see table 9.2). Recently the most rapid rates of increase within this sector have been in finance, insurance and real estate (FIRE), service: community business and public service; public administration and defence; and trade. The projections of the System Research Group (SRG) in table 9.3, based on a log-linear extrapolation with stepwise normalizing of the percentages, present national fore-

164

Urban futures for Central Canada

TABLE 9.2 Canada: Percentage distributon of employment by industry, 1946-66 1946 Agriculture Forestry and fishing Mining, quarrying, oil wells Manufacturing Construction Transportation and utilities Trade Finance, insurance, and real estate Service TOTAL

1966

1956

24.8

13.6

2.3 1.5

2.4 2.1

7.4 1.4 1.7

25.3

25.1

24.8

4.7 7.9

7.2 8.8

7.5 7.7

12.0

15.5

15.6

2.6

3.4

4.2

18.9

21.9

29.7

100.0

100.0

100.0

SOURCE Economic Council of Canada 1968 TABLE 9.3 Canada: Percentage distribution of employment, 1961 and projections for 1971-2001

Agriculture Fishing and trapping Forestry Mining Manufacturing Construction Transportation and utilities Trade Finance Service Public administration

1961

1971

1981

1991

2001

11.5 0.3 1.3 1.9

5.9 0.4 0.9 1.6

2.8 0.3 0.6 1.3

1.3 0.3 0.4 1.0

0.6 0.2 0.2 0.8

22.7

23.2

22.4

21.0

19.3

6.0

6.2

5.9

5.4

4.8

10.3 16.0

8.9

7.4

5.9

4.6

15.9

15.1

13.7

12.1

3.6

4.2

4.7

5.0

5.2

20.9

27.5

34.5

41.5

48.5

5.6

5.4

5.0

4.4

3.8

SOURCE SRG, 1970

casts to 2001. Tertiary activities augment their present share of about 62 per cent to over 74 per cent of employment; primary and secondary sectors both supply the relative shares shifted to the services. But there are differences within the tertiary sector - the community, business, and personal service industry, for example, appears to show the consequence

Forecasting Ontario's regional economy

165

of low productivity levels by its expected substantial increase in employment from 28 to 49 per cent of national employment. The Ontario projections for 2001 are not radically different from those produced by SRG for Canada (table 9.3); nevertheless present structural differences do emerge from the comparison. The more important shares projected for the manufacturing and service industries in Ontario are very much a reflection of the greater degree of urbanization of the province. REGIONAL LABOUR FORCE PROJECTIONS Projections of the labour force in Ontario for ten economic regions (see figure 9.1) have also been made by DTE independently of the sectoral employment forecasts. The regions

Figure 9.1 Ontario economic regions, 1972 used in this forecast are those that have been employed in other official economic compilations in Ontario. Labour force estimates for these economic regions are determined by applying regional age-sex disaggregated participation

166

Urban futures for Central Canada

rates to the working-age population in each region in each time period. Population forecasts are first obtained by applying appropriate age-sex disaggregated mortality, fertility, and migration rates to the population of each region in the initial period. The accuracy of these population forecasts depends particularly on the assumed rate of net migration to Ontario and, in fact, the DTE was forced to reevaluate its 1964 forecasts in view of the increased inmigration to Central Ontario,3 and on the basis of information concerning regional variations in participation rates, which was made available on a small-area basis for the first time in 1961. The most important aspect of participation rates for labour force projection is the change that has occurred in the proportion of women working. Sectoral change, urbanization, and the return of married women to the labour force have all been described as influences giving rise to greater opportunities for women. The proportion of women in the Canadian labour force has been progressively approaching the prevailing US rate of 43 per cent. The labour force participation rates developed by SRG for Ontario are listed by age group and sex in table 9.4. These rates were obtained by extending the 1966-86 rates projected by Illing (1967) for the Economic Council of Canada.4 The most striking change in participation rates is the substantial increase expected for women in the 25-64 age group (Canada Department of Labour 1971). These rates are expected to increase dramatically until 1976, tapering off only slightly from 1981 to 2001. Participation rates for males in all age groups except the over 65 group are projected to remain fairly constant over the entire period from 1971 to 2001. Earlier retirement is likely to cause a decline in the participation rates of males over 65. The participation rates were corrected for regional variations estimated by DTE. In general the more highly urbanized parts of the province, particularly Central and Midwestern Ontario, have higher rates than all other regions in most categories. By multiplying the participation rates by the regional population forecasts for the economic regions estimates of the future regional labour force for 1971-2001 are obtained (see table 9.5). Increases are expected in all regions of Ontario to 2001 but are largest in the urban axis from Windsor through Kitchener-Waterloo and Hamilton to Toronto, including the economic regions of Lake St Clair, Midwestern Ontario, Niagara, and Central Ontario.

Forecasting Ontario's regional economy

167

TABLE 9.4 Ontario: Projections of labour force participation rates, 1971-2001 Age group

1971

1981

1991

2001

65+

37.3 83.4 98.5 99.0 99.0 90.4 26.2

36.7 82.4 98.5 99.0 99.0 89.8 23.0

37.0 82.2 98.5 99.0 99.0 89.2 19.5

37.9 82.0 98.5 99.0 99.0 88.6 16.1

FEMALES 14-19 20-24 25-34 35-44 45-54 55-64

30.9 57.6 37.6 42.6 45.7 36.4

31.2 60.3 41.8 49.7 53.2 43.8

32.6 62.3 44.9 55.6 59.5 50.1

34.0 64.2 47.9 61.1 65.9 56.4

6.9

7.9

8.5

9.2

MALES 14-19 20-24 25-34 35-44 45-54 55-64

65+

SOURCE SRG, 1970

TABLE 9.5 Labour force projections by economic region, 1971-2001 Region

1971

1981

1991

2001

Eastern Ontario Lake Ontario Central Ontario Niagara Lake Erie Lake St Clair Midwestern Georgian Bay Northeastern Northwestern

380410 141300 1286410 371040 199640 206660 198540 132870 209260 91680

484310 174760 1743610 465250 250730 269600 252700 156890 268550 111480

574540 197700 2161730 542140 293650 322780 296580 171400 305440 123140

674680 228810 2606310 621620 341640 384770 345820 185570 342670 135300

TOTAL

3217810

4177880

4989100

5867190

168

Urban futures for Central Canada

SECTORAL EMPLOYMENT Ideally employment data are used to measure the level of economic activity, rather than the labour force. However the labour force data, by both region and sector, published in the 1951 and 1961 Censuses include not only employed persons but those actively seeking work. In order to establish the logical relationship between (1) the sectoral and regional breakdowns of the labour force enumerated by the census, (2) the regional labour force estimates for Ontario from 1971 to 2001, and (3) the sectoral employment projections of Ontario from 1971 to 2001, it is necessary to augment the sectoral forecasts by the amount of unemployment in each sector. This, of course, follows from the identity that employment plus unemployment equals labour force. In the absence of any detailed statistics concerning the rate of unemployment by activity sector in Ontario the rates of all sectors have been assumed equal. For the purposes of projection a longterm unemployment rate of 3.5 per cent was estimated from a 25-year (1954-69) series of unemployment rates for Ontario. This figure can be compared to the 4 per cent rate used by SRG for Canada as a whole. The resultant control totals for 1971 to 2001 are detailed by activity sector in table 9.6. METHODOLOGY IN PROJECTION OF THE REGIONAL-SECTORAL LABOUR FORCE For each region and sector the change in the labour force from 1951 to 1961 was extrapolated to 1971. These preliminary projections can then be normalized on the basis of the control totals of each region (table 9.5) and each sector (table 9.6). In the next iteration, to 1981, these revised 1971 estimates are also included in the log-linear determination of least squares estimators. This iterative method of estimating labour force based on sectoral and regional labour force control values is an especially conservative form of projection in that no region or sector can depart from the aggregates that have been independently projected. The assumptions that underlie this type of projection are the usual ones of continued motion of a pattern of change a pattern that is, in this case,particularly poorly defined in terms of reliable regional and sectoral data. The use of a normalizing routine in adjusting these projections at each year assumes, of course, that their accuracy exceeds

Forecasting Ontario's regional economy

169

TABLE 9.6 Ontario: Labour force projections by sector, 1971-2001 Sector Agriculture Forestry and fishing Mining Manufacturing Construction Transportation and utilities Trade Finance, insurance, and real estate Service Residual TOTAL

1971

1981

1991

2001

140960 15280 29960 917080 201700 222500 519880

100820 14260 26720 1120830 200110 246350 677500

70260 12750 21420 1245000 182190 249350 792840

44350 10780 16840 1320000 157780 239340 894700

139280 961840 69330

193040 1509880 88010

237310 2072250 105630

282850 2785810 114720

3217910

4177880

4989100

5867190

that of any combined regional-sectoral forecast. It has already been emphasized that provincial estimates are likely to be more accurate merely because of the superior data available at that level of aggregation. The projections The labour force projections, by region and sector, are presented in table 9.7. In general they reflect (1) the decreasing importance of primary activities, (2) the substantial increases in service employment in all regions, and (3) the initial regional sectoral structures. In Eastern Ontario, for example, agricultural activity is projected to decline from just under 9 per cent in 1961 to only 1 per cent in 2001. This reflects the provincial (as well as national) trend towards substantial absolute decreases in most primary activities. In 1961 the proportion of Eastern Ontario's labour force in services was almost double that of any other economic region, reflecting the importance of federal government activity. It is expected that the region will retain this characteristic to 2001, but rapid service expansion will occur in all regions over the next three decades. In 1961 Central Ontario had a labour force structure closely approximating the provincial average, reflecting the tendency for metropolitan areas such as Toronto to have a diverse employment structure. This pattern is replicated in the projections to 2001; Central Ontario has neither the

TABLE 9.7 Ontario labour force:

Projections, 1971-2001; regional proportions by sector

Year Region

AgriForestry Mining Manufac:- ConTransTr adej5 cultur e and turing struc-- portati*Dn f ishing and tion utiliti es

1971 Eastern Lake Ontario Central Niagara Erie St Clair Midwestern Georgian Bay Northeastern Northwestern

4.9 7.0 1.0 3.4 13.0 10.1 9.4 13.8 1.5 1.0

0.5 0.3 0.0 0.0 0.1 0.2 0.0 0.4 2.9 5.5

0.2 1.2 0.3 0.2 0.1 0.5 0.2 0.1 9.4 1.4

16.1 21.6 29.6 39.4 27.5 29.4 39.2 23.5 18.8 21.9

7.2 6.4 5.6 6.2 5.6 6.7 6.5 7.6 6.9 8.3

6.3 6.0 7.4 5.3 5.3 5.9 4.6 8.3 9.4 14.2

13 .5 15 .5 17 .3 15 .3 16 .2 15 .7 14 .8 16 .1 17 .7 16 .7

3.5 1.9 6.3 2.9 4.1 3.5 3.2 2.0 2.6 2.2

44.1 22.7 29.5 25.9 27.3 27.4 21.4 27.8 29.0 28.2

3.8 0.4 311 1.4 0.9 0.8 0.8 0.3 1.8 0.6

1981 Eastern Lake Ontario Central Niagara Erie St Clair Midwestern Georgian Bay Northeastern Northwestern

2.4 2.8 0.5 2.0 8.3 7.4 5.1 7.3 0.5 0.3

0.5 0.2 0.0 0.0 0.0 0.2 0.0 0.4 2.1 3.5

0.1 1.4 0.4 0.1 0.1 0.7 0.3 0.1 4.6 0.3

15.5 32.0 26.7 35.9 30.0 24.8 40.8 26.6 17.1 23.5

6.0 4.2 4.4 4.8 4.0 5.4 5.1 5.5 4.9 3.1

5.5 5.0 6.3 4.4 4.2 5.1 4.1 8.2 7.7 10.3

13 .7 16 .2 16 .0 15 .9 16 .6 16 .2 15 .9 18 .2 20 .7 18 .2

3.8 1.7 6.3 3.2 4.5 4.6 3.4 2.3 3.3 2.2

49.0 36.4 35.6 33.2 32.2 35.4 25.2 31.4 38.7 36.8

3.5 0.0 3.8 0.6 0.2 0.2 0.2 0.0 0.4 0.0

Finance, Serinsurvice ance, and real estate

Residual

Table 9.7 continued Year Region

Trades> Financ e, SerAg:riForest:ry Mining Manufac:- ConTranstaring insurvice cu Itur e and struc-- portation ance, fishin 0.95) established in previous cross-sectional studies between developed area and population (Maher and Bourne, 1969). However this method assumes that land area increases in a linear fashion with city size, and thus takes only partial account of future growth, and that per capita rates for a given size of city remain constant over time. The latter assumption is the more suspect as it ignores, or at least obscures, the future impact of technological innovations and policy incentives. Also it ignores significant variations

218 Urban futures for Central Canada TABLE 12.2 Estimated total area in urban use, Central Canada, metropolitan areas, 1971-2001 (in acres) 1951

CMA

Hamilton

1961

High Median

Kitchener

21009

8966

89742 59924 51674

28489

26823 21208 19138

39660 26243 22595

38007 31091 26307

12447

18058 16628 16217 17243

25208 21605 19742

34477 25920 22792

46378 30206 25726

14278

18464 17651 17175 21274

55848 47933 36215

77022 57658 42339

102826 66602 48112

30712

40493 38925 30586 41002

17107 13226 9336

25532 15735 9040

36462 18194 8445

9262

11518 10942 9557 12376

232797 170566 142878

356013 234594 158719

530698 278236 172236

110357

154420 147478 130272 151546

21605 20076 16148

26243 22792 15597

31218 25208 14974

15113

17787 17583 16286 19339

220014 197928 180500

301388 246888 217172

405950 299696 270193

125543

162341 158157 154676 157442

43127 40088 34788

56608 47575 38250

74492 54853 40942

26114

33416 32978 31281 33604

High Median

Low Actual Ottawa

10580

High Median

Low Actual Sudbury

21870

High Median

Low Actual Toronto

6469

High Median

Low Actual Windsor

76742

High Median

Low Actual Montreal

13085

High Median

Low Actual Quebec

91281

High Median

Low Actual

20743

2001

67459 51496 45898

Low London

1991

49303 42885 39415

High Median Actual

1981

36401 35037 34040 34850

Low Actual

1971

Trends in future urban land use

219

Table 12.2 continued

CMA

1951

1961

1971

Total acreage for metropolitan areas High 492801 Median 475383 Low 440092 Actual 270745 372318 488681

1981

1991

2001

691834 575517 498164

984403 1422154 728904 864014 572407 658611

TABLE 12.3 Estimated total area in urban use, Central Canada, major urban areas, 1971-2001 (in acres)

MUA Brampton Brantford Cornwall Guelph Kingston Niagara Falls Oshawa-Whitby Peterborough Sarnia Sault Ste Marie St Catharines Thunder Bay Timmins Welland Chicoutimi-Jonquiere Drummondville Granby St Jean St Jerome Shawinigan Sherbrooke Trois Rivieres Valleyfield Total acreage

1951

1961

1971

1981

1991

2001

903 4329 1760 2823 4410 3836 4572 3753 3753 3586 5925 6003 3503 2299 6624 3335 2211 2476 1851 4572 4975 5846 2388

1851 5135 4083 3919 5610 4975 7008 4572 5452 5214 8145 7919 3753 3419 8818 3670 2995 3335 2823 5689 6159 7237 2909

5373 5925 5294 5135 6855 6003 10216 5373 6547 7237 10144 9041 4001 5846 9778 4083 4001 3919 3919 5768 7616 9115 3586

7314 6778 9041 6003 8070 7237 13999 6081 7844 8669 12305 10653 4491 7085 9998 4653 4814 4814 4814 5532 9115 9851 3836

11231 7616 12447 7008 9262 8519 18262 6855 9189 10289 14697 12376 5055 8370 10144 5214 5610 5768 5768 5135 10653 10508 4083

14418 8370 15113 7919 10435 9778 20478 7542 10508 11734 16971 14069 5610 9631 9778 5689 6314 6778 6778 4572 12234 10870 4165

85733

114690

144776

172512

203026

228031

220

Urban futures for Central Canada

between cities in density and land utilization. Ideally we need a range of differing assumptions regarding both anticipated total population growth and changing rates of land utilization. Following the methodological alternatives outlined above, we proposed the following spectrum of forecasts (figure 12.1). For each range of population forecast we have varied the assumption regarding per capita rates of land utilization. The result is nine different estimates for each city, for each province, and for all cities in Central Canada taken together. Needless to say, we cannot reproduce this information here. Moreover this range of alternatives ignores different assumptions regarding policy effects and varying spatial configurations. Extending this approach to its logical conclusion, even in the narrow terms of land use, would lead to a situation similar to Doxiadis's 49 million alternatives for the Detroit region. Such an exercise is pointless. Instead we have selected only a few of the more revealing and realistic forecasts as the basis for discussion.

Figure 12.1 Range of alternative land-use forecasts

Trends in future urban land use

221

Table 12.4 summarizes two alternative land-use forecasts for the 63 largest cities in Central Canada identified in previous studies. The first, projection A, is based on the equation cited above and is in fact the total of all cities in tables 12.2 and 12.3, as well as all other smaller centres with populations over 10,000 in 1966. The second, projection B, is one of three sets based on the same population totals as above but employing the moderately declining rate of per capita land consumption noted earlier. TABLE 12.4 Estimated total area in urban use,

Central Canada, 1951-2001

Year

Estimated acres (OOOs)

1951

395.9

% change in acres

63

36.4 1961

540.2

PROJECTION A 1971

High Median 703. 8 686.4

1981 1991

953.0

63

836.7

1301. 8 1046.3

Low 651 .1

30.3

27.1

20.5

35.4 21.9

16.6

36.6 25.1

18.0

63

759 .3

63

889.8

63

37.7

2001 PROJECTION B 1971

1793. 2

1235.1

1029 .7

765. 6

742.1

678 .2

1991 2001

900. 7

1147. 5 1483. 4

764.3

874.1 964.3

18.0 15.7 63 63

17.6

1981

Number of cities over 10,000 population in forecast

3.0

2.5

27.4 14.4

2.7

29.3

7.9

695 .3

63

713 .9

63

10.3

770 .3

PROJECTIONS A: based on the relationship between developed area and total population; B: based on the declining rate of land utilization per capita. Both projections use the estimated future population totals summarized in paper 3 in this volume.

The range of land-use estimates is enormous. By the year 2001 the difference between high and low estimated acreages is nearly 100 per cent. Even so, the figures are plausible

222

Urban futures for Central Canada

as descriptions of alternative futures under their specific assumptions; there is little basis for evaluation or comparison, since no one really knows how much land in Canada is in urban use at present. Several significant trends are apparent. First, with one exception (projection B, low), all forecasts point to a substantial increase in urbanized land area within Central Canada. To what extent this is or will become a problem varies, of course, with the area and with local conditions. Relative to the total area of the region, furthermore, these figures represent an almost insignificant proportion. Yet in the major metropolitan regions - the urban complex around western Lake Ontario, the Montreal region, and the NiagaraGrand River areas, the potential problems are obvious to any observer monitoring landscape change, agricultural resources, and environmental quality in Central Canada (see Russwurm, 1970; Beauregard, 1972). The second point is that land use appears to be, given the data and methods employed here, more sensitive to assumptions regarding the distribution of total population than to differing rates of land utilization. This partly reflects the degree to which the assumptions were allowed to vary, yet it also suggests that, given Canada's comparatively rapid growth, the distribution of population increments rather than changes in densities and technology will largely determine the future physical form of our urban areas. It is also significant that population distribution, on a regional basis, is the component of urban growth over which, as Blumenfeld noted earlier, public policy is likely to have its principal influence, if any, in future decades. A third consideration follows from our awareness that densities tend to increase systematically with city size and that therefore, overall land-utilization rates fall. This suggests that the increasing concentration of Canada's population in metropolitan complexes will contribute to a lower rate of rural land absorption in the future (table 12.5). This, however, is small compensation, and must be balanced against the fact that the impact of the metropolis spills far beyond its boundaries and beyond its physical imprint in terms of land use. Also the quality of rural land lost tends to be higher in the larger metropolitan regions. Needless to say, it is these questions of overspill and of differential impact which contain the major unknowns in forecasting urban land use.

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223

TABLE 12.5 Total land in urban use, by size of city, Ontario and Quebec, 1961-20011

Population of city

Actual 1961

1971

1981

MOO, 000 50-100,000 25-50,000 10-25,000

348. 6 104.9 74.6 106. 9

499.9 104. 5 106. 5 76.3

622. 1 124. 7 108. 5 57. 5

837 .9 135 .1 76 .8 59 .6

1024 .9 134 .4 91 .6 48 .5

Total 63 cities (000 acres)

635. 0

787.2

912. 8

1109 .4

1299 .4

1991

2001

1 Based on median population projections (table 3.2) and rates of land absorption noted in Bourne and Doucet (1973).

If the problems of definition and measurement in land use at the aggregate urban system level are annoyances, they represent a formidable problem in specifying the form of the individual urban region. This level is also the one at which public policy may have its greatest direct impact. In this section we briefly examine trends in land-use composition, and in the spatial configuration of land-use change, within metropolitan regions. Most of our empirical examples are drawn from Toronto data. Land-use composition The composition of land use varies widely among Central Canadian cities (Maher and Bourne, 1969). Any discussion of trends specific to a given city must concern itself largely with marginal increments to existing areas rather than with direct attention to given uses in the aggregate. The rate of 'land utilization1 per capita is the best such measure; and the marginal rate (per capita of population increase) is the best indicator of trend changes. Gross land-use figures1 for 1958, 1963, 1966, and 1968 by major planning district were obtained from the Metropolitan Toronto Planning Board (MTPB) for all major land-use categories. For each survey period land use in each category was expressed as a percentage of the total land area of each of 301 census tracts (traffic zones) and 24 planning districts. The averages of these percentages for planning dist-

224

Urban futures for Central Canada

ricts are shown in table 12.6, along with percentages given by Niedercorn and Hearle (1963) for US cities (where applicable) for comparison. TABLE 12.6 Mean proportions of land devoted to various uses in Metropolitan Toronto (average of planning districts, n = 16)

Land -use category

Percentage of total land (gross) 1966 1968 1958 1963

Niedercorn and Hearle (net) US cities

Residential Industrial Commercial Open space Institutional Transportation Vacant

32.94 6.29 3.11 13.49 3.81 6.74 33.57

40.73 8.25 3.26 13.56 5.44 7.89 20.14

29.6 8.6 3.7 Categories are not comparable 20.7

36.86 7.05 3.63 13.94 4.34 7.34 26.84

39.89 7.93 3.88 14.05 4.88 7.64 21.71

As a percentage of the total area, the residential, industrial, institutional, and transportation categories are increasing through time. In fact, the first three categories have increased at the same rate over the ten-year period. In general, the trend in utilization rates for each landuse type over time closely approximates a hyperbolic function of the form Yj = X/(ajX

+ bj) ,

where Y is the utilization rate for each of j land use categories, X is the year, and a and b are empirically determined parameters. The resulting curves derived for each type of land use are shown in figure 12.2. General trends can be extrapolated from the two fiveyear periods of 1958 to 1963 and 1963 to 1968 - even though significant variations from these trends were observed in the shorter periods from 1963 to 1966 and 1966 to 1968, for which data are available. These variations obviously are due to short-term fluctuations in demand-supply responses, and to the complex time lags between population change and land-use change. Residential and industrial marginal utilization rates show a general increase; the marginal rates projected by the MTPB agree with this trend (MTPB, 1970), but are considerably higher for other uses.

Trends in future urban land use

225

Figure 12.2 Existing and projected trends in land-utilization rates from 1958 to 2001 The marginal utilization rates for open space, transportation, and total developed area have shown a significant decrease; commercial rates have shown a slight, but evident, decrease. The projected marginal utilization rates for the open space and transportation categories decline dramatically in Figure 12.2 within Metro Toronto and, if present trends continue, will be seriously depleted by 1980-5. The projected rate for commercial uses is contrary to the results of our analysis of existing trends. The marginal utilization rate for institutional land has shown a slight increase during the past ten years, and is projected to increase further but at a decreasing rate in the future. These trends in utilization rates, either absolute or marginal, are perhaps the most significant indicators of

226 Urban futures for Central Canada land-use growth and change. Although they are subject to numerous unknowns, and the problems of forecasting based on a single time series are obvious, their variation through time and between categories of land use does reflect the changing values of the population. The decline in absolute utilization rates for all categories (except institutional) reflects the trend towards high density offices and highrise apartment living and reduced space needs, and is exaggerated by our use of a fixed metropolitan boundary. The major investments in educational and other public facilities in the 1960s are reflected in the increasing utilization rate for institutional land. The marginal rates reflect these same trends, but to a lesser extent, since wide temporal variations are evident. A reversal of the trend toward the low-density sprawl typical of the 1950s is indicated, and recent trends evident from the Toronto data suggest a more compact, higher-density Canadian city in the future. The spatial configuration of land-use change The spatial structure of land-use change within cities, by type of use is even more complex. We have found, however, in previous research, (Bourne, 1973; Bourne and Doucet, 1973) that only four spatial components of land-use growth need be modelled. These four, with their respective components, are: No.

Component/subcomponent

No.

1

Suburban-fringe growth

1

(a) residential subdivision units (b) open space (c) institutional-industrial complexes

Spatial pattern and landuse characteristics Concentric pattern, all uses

(a) residential, local retail, and service uses (b) open space-recreational (c) large, single-function developments

Core-area growth: 2 Localized areal expansion renewal (a) expansion of the CBD fringe (b) renewal of core of the CBD

(a) redevelopment of outlying locations (b) higher density office/ commercial uses

Trends in future urban land use 3

Infrastructure growth

3

(b) public utilities Nucleations growth (a) (b) (c) (d)

government institutions hotels apartments

Network pattern, service uses (a) new expressway developments (b) water, hydro, electricity, etc.

(a) expressway system

4

227

4

Scattered nucleations, single uses (a- large, single-purpose d) developments often under single ownership

Although these are specific in their construction to Metropolitan Toronto, and to changes in the 1960s, parallel examples can be drawn for Montreal (Foggin, 1972). It is the relative balance of these four components of the 'physical1 urban growth process which will determine the future form of the urban area. While we do not have sufficient time-series data to place absolute weights on each, it is clear that these weights have shifted in the past and will do so again in the future. In the 1950s and early 1960s, at least in Toronto, the suburbanization component dominated. In the mid to late 1960s the emphasis shifted somewhat to renewal of the core (with major private and governmental investments taking a much larger share), as well as to the proliferation of high-density redevelopment nucleations at strategic locations outside the central core (Simmons and Bourne, 1972). More recently the trend has again been reversed. Growth of the fringe, and in particular expansion of outlying communities, has accelerated as developers respond to the increasing difficulties facing redevelopment schemes. Obviously this behaviour is cyclical, reinforcing and accentuating the family of growth 'cycles' which characterize and imprint the modern city (Whitehand, 1972). We are not in a position at this point, but could be with a further complement of land-use data, to undertake statistical extrapolations of the balance of all of these growth factors. Yet to ignore their existence is to fail to grasp the complexity of change in the spatial structure of our cities. These are the components which we must monitor in

228

Urban futures for Central Canada

anticipating alternative urban land-use futures. In the following section we examine one such component, and the appliccition of one type of forecasting methodology. REDEVELOPMENT AND THE FUTURE OF THE CENTRAL CITY Often overlooked in evaluating past land-use change is the effect of redevelopment. In its broadest sense redevelopment refers to both the rearrangement of activities within the city and the wholesale rebuilding of major tracts. As the pressures on available and 'undeveloped1 land in the major metropolitan regions continue to rise, the importance of redevelopment increases. In fact within large cities in Canada redevelopment is now a paramount political issue in the debate on the future of the city (Lorimer, 1972). The impact of redevelopment What do we know about recent redevelopment trends? What if anything do these trends indicate about future urban forms? Here data are even scarcer. There has been no comprehensive empirical analysis of redevelopment in any Canadian city; only limited forays into small areas based on incomplete data sources (Bourne, 1970; Gayler, 1971). Yet we do know that, redevelopment has had a significant but selective impact. One need only examine the skyline changes in Montreal in the early 1960s, in Toronto in the late 1960s, and more recently in the Londons, Hamiltons, and Quebecs. But the skyline view is misleading. It says little about the multitude of smaller changes through redevelopment which are not reflected in high-rise concrete and glass (or parking lots), but which in total contribute to the future structure of the city. We also know that redevelopment has shown dramatic shifts in location, type, and impact over time. The historical path of redevelopment is in fact cyclical, resembling the boom-bust history of land development on the urban frontier. It depends largely on forces external to the individual city, such as interest rates, capital flows, the balance of growth and non-growth industries, but also increasingly reflects the local political climate. This cyclical pattern may or may not correspond to national building and construction cycles; and each peak tends to emphasize different types of projects and to hit different locations within the city and is thus highly unpredictable.

Trends in future urban land use

229

Figure 12.3 demonstrates this cyclical behaviour using the simple example of residential demolitions in Toronto. These represent one expression of redevelopment - in which both private and public agencies play a prominent role. Although it is not practical to assign these demolitions to a particular cause, it is clear that substantial modifications of the existing urban structure can take place in a relatively short period of time. Raymond Vernon's pessimistic prediction in the 1950s that the 'grey1 areas extending in wide arcs about the centres of most North American cities will persist for decades is clearly open to question in the Canadian context.

Figure 12.3 Profile of demolitions in Toronto One of the difficult aspects of evaluating land use change through redevelopment is measuring the actual extent of the reuse of land. This is of course what redevelopment means. One approach, which has been described in detail elsewhere (Bourne, 1969), employs a standard type of model to allocate future units of growth to subareas within the city, which are then linked to a matrix denoting the probabilities of land conversion within each subarea. One result, summarizing forecasts of land use change for the City of Toronto is given in table 12.7. Only the forecasts through 1982 are in a limited sense statistically valid, although the others at least warrant inclusion here as a basis for more general discussion. Two aspects of these forecasts are worthy of note. One is the persistence of the general land-use structure of the city through several decades of renewal and redevelopment.

230

Urban futures for Central Canada

TABLE 12.7 Forecasts of land use, 1972-2002, City of Toronto, total acres (using sequential-transition probability matrices)

Land -use category Low-density residential High-density residential Office commercial General commercial Auto commercial Parking Warehousing Industry Transportation Vacant

Actual 1962

Forecast 1972 1982

1992

2002

7634 .09

7416. 31

7202.00

6781 .86

6420 .16

377 .24 267 .38 633 .51 215 .02 336 .69 1012 .67 1014 .39 14 .59 533 .66

488. 41 340. 71 660.54 275. 89 484. 20 998. 46 1062. 37

551. 44 434. 98 691. 29 374. 16 638. 36 980. 80 1103. 26

16.25

17.94 45.02

593 .99 520 .95 703 .28 479 .73 111 .83 934 .48 1106 .09 19 .02 122 .00

638 .16 608 .44 720 .88 592 .93 915 .25 890 .92 1109 .55 20 97 1 • 1 122 .oo

296. 09

1 Constraint added to maintain a minimum level of vacant land, reflecting the time required between demolition and new construction, in this instance set at 1 per cent of the developed area.

Yet, despite this 'inertia1 in urban real estate, the growth in area of specific functions is substantial: high-density residential and commercial at one end of the density scale; parking and related 'machine-oriented' uses at the other end. These forecasts clearly reinforce those based on the logistic extrapolation discussed previously. In both office and parking uses the forecast calls for nearly a 100 per cent increase in area by the turn of the century. What of future trends in redevelopment in general? Clearly the rate of redevelopment in terms of land area will decline in the next decade, and likely more so in the following two decades. It will not continue at present rates for three basic reasons: 1

The densities at which new projects are undertaken has increased and will continue to rise in the future, thereby reducing the land area requirements for a finite space demand for most core area functions and locations. 2 The mixed social benefits of massive redevelopment has led to awakened community response and concern. Many potential sites have as a result been removed from the developers' map of alternatives.

Trends in future urban land use 3

231

Third, and possibly most significant, the demand for redevelopment will slacken. It will do so because of slackening population growth, greater environmental control, shifting social priorities, and increased rehabilitation and restoration among the existing stock.

Consequently redevelopment will be more purposeful, more selective, and possibly more orderly. It need not be disruptive, as one of the basic problems is the misuse or underuse of urban land, for which redevelopment would be an economic and environmental improvement. The future of the central core Given the trends outlined previously in this paper, what sort of physical urban form may emerge for the downtown 'core' area? In terms of land use, densities of redevelopment will continue to increase as buildings grow in size and sitecoverage restrictions are relaxed or bartered for environmental-design concessions from the developer. The redevelopment process will clearly become even more selective in its choice of site. Only a few buildings of historical or architectural merit will be spared, and even these will need more effective policy machinery than is presently available if they are to survive. The scale of change in land use documented in the previous section is further emphasized for the central core area by figures on the growth of floor area (table 12.8). Although these data sources are not compatible with those in previous sections of this paper, they do reveal the same general shift to higher-density commercial uses and away from warehousing, industry, marginal retail, and similar low-density activities. In this example between 1969 and 1989 total floor area within the Toronto core is expected to grow by at least 70 per cent. Employment within the core will increase in concert with new building construction. The general concensus seems to be that, by 1980, more than 173,000 people will be employed in the core of the Toronto CBD, an increase of 40,000 since the early 1960s. As most of this employment will be associated with the 9 am to 5 pm working day, the movement of traffic within and through this area will increase. Certain functions will be forced out of the centre to other developing high-density nodes further away. It will also become necessary to close some streets to traffic during peak hours, particularly if retail functions are to survive, and to

TABLE 12.8 Forecasted floor-space distribution in the urban core:

Toronto CBD

Year

Thousands of sq. ft., usable floor space in core area InstiResitutions Industry Utilities Apartments dential Office

1969 1974 1979 1989 A 1989 B

104.1 769.9 1116.5 2516.5 4616.5

3680.4 6051.9 6450.0 9100.0 8450.0

1775.5 1757.6 1810.3 1810.3 1810.3

1969 1974 1979 1989 A 1989 B

Percentage of total area in each use 8.15 52.62 0.23 0.28 11.01 1.40 1.58 50.81 1.92 54.10 11.11 1.48 13.78 3.81 1.30 51.46 10.97 56.33 5.99 1.11

3.92 3.19 3.12 2.74 2.35

129.2 871.6 861.9 861.9 861.9

23748.3 27925.7 31383.8 33983.8 43383.8

Warehousing

Retail

Other

TOTAL

46.3 68.3 65.9 65.9 65.9

3879.1 3823.1 2973.8 2973.8 2973.8

10753.4 12675.1 12384.7 13759.7 13884.7

1007.1 1007.1 962.2 962.2 962.2

45123.4 54950.3 58009.1 66034.1 77009.1

0.10 0.12 0.11 0.09 0.08

8.59 6.95 5.12 4.50 3.86

23.83 23.06 21.34 20.83 18.02

2.23 1.83 1.65 1.45 1.24

Forecasts are based on proposals submitted to the Buildings and Development Department, City of Toronto, by 1 October 1971 and unpublished forecasts made by the City of Toronto Planning Board. A minimum and maximum forecast is given for the period 1979-89. 1 Defined as Census Tracts 73, 74, 75, and 76: and the waterfront

an area bounded by College, Simcoe, and Jarvis streets

Trends in future urban land use

233

create more multilevel systems of accessibility into and within the core. Parking rates will continue to rise; additions will be made to certain subway stations to handle the increased peak-hour loads, new intermediate-capacity transport systems will be introduced, one-way streets will be common, and scheduling of servicing will be essential. Developments in the core tend to be lumpy, and the unknowns more numerous and of larger variance than in other areas of the city. Available data are frequently compiled in such a way as to mask certain trends which are obvious to anyone who passes through this area. Nevertheless most of the major projects which will form the core of the city, at least in 1985, are now underway either in fact or in concept. The difficult question is generally one of timing. What other changes can we expect to find in this area? A dominant feature of the core of the future, will undoubtedly be the phenomenon of the so-called multi-complex, multiorganization development. Land costs, taxes, and scale economies have combined to encourage a corporate approach to redevelopment. It is the large-scale developer or public body who will make the greatest contributions to the shape and content of the future core. Several such corporate 'complexes1 are already under construction or in the planning stages in Toronto: the Eaton Centre, the Campeau waterfront development, and Metro Centre. Similar developments are underway in Montreal (Beauregard, 1972). Many of the Toronto projects are located outside the inner core of the CBD as it is defined here (see table 12.8), and most are mixed residential and commercial ventures. In fact much of the future form of the entire core will depend on the nature and rate of development on the Toronto waterfront. The two most difficult unknowns in attempting to forecast core-area growth or future land use generally are changes in social attitudes and planning constraints. Neither is likely to shift dramatically within the immediate planning horizon, yet the increasing concern for social and environmental problems will no doubt find its greatest expression and influence in the core areas of the major metropolitan areas and in their immediate residential fringes. One cannot readily anticipate the sorts of controls that planning agencies and community groups will be able to exercise in the future, but they will be greater. While the cycles of redevelopment are not easily stopped or relocated, recent signals indicate several alternative redirections are

234

Urban futures for Central Canada

possible - the most likely at present is for a stronger core for Toronto and for most other cities in Central Canada. NOTES *

1

This paper draws heavily on data compiled under grants from the Canadian Council on Urban and Regional Research and the Central Mortgage and Housing Corporation. We gratefully acknowledge this support. Gross land use figures in this instance include roads and streets with the adjacent land use category. We should also thank the Metropolitan Planning Board and the Metropolitan Toronto and Region Transportation Study for permission to use these data.

REFERENCES Beauregard, L. 1972. 'Montreal: The Year 2000,' in L. Beauregard, ed., Montreal Field Guide. Montreal: Les Presses de 1'Universite de Montreal. Pp 193-7 Best, R.H. 1964. 'The Future Urban Acreage,1 Town and Country Planning, 31: 350-5 Best, R.H., and Champion, A.G. 1970. 'Regional Conversions of Agricultural Land to Urban Use in England and Wales, 1945-67,' Transactions Institute of British Geographers, 49: 15-32 Best, R.H., and Rogers, A.W. 1973. The Urban Countryside. London: Faber Bourne, L.S. 1969. 'A Spatial Allocation-Land Use Conversion Model of Urban Growth,' Journal of Regional Science, 9/2: 261-72 Bourne, L.S. 1970. 'Trends in Urban Redevelopment: The Implications for Urban Form,' Appraisal Journal, 38/1: 24-36 Bourne, L.S. 1973. 'Descriptive Models of Urban Land Use: A Summary,' in L.S. Bourne, et al., eds, The Form of Cities in Central Canada: Selected Papers. Toronto: University of Toronto Press Bourne, L.S., and Doucet, M.J. 1973. 'Components of Land Use Change and Physical Growth,' in L.S. Bourne, et al., eds, The Form of Cities in Central Canada: Selected Papers. Toronto: University of Toronto Press Brown, H.J., et al. 1972. Empirical Models of Urban Land Use. New York: Columbia University Press Clawson, M. 197la. Suburban Land Conversion in the United

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States. Baltimore: Johns Hopkins University Press for Resources for the Future, Inc. Clawson, M. 1971b. America's Land and Its Uses. Baltimore: Johns Hopkins University Press Dahinden, J. 1972. Urban Structures for the Future. New York: Praeger Foggin, P. 1972. 'Urban Land Use Patterns: The Montreal Case,' in L. Beauregard, ed., Montreal Field Guide. Montreal: Les Presses de 1'Universite de Montreal. Pp 32-45 Gad, Gunter. 1973. 'Problems in Measuring Urban Expansion,' in L.S. Bourne, et al., eds, The Form of Cities in Central Canada: Selected Papers. Toronto: University of Toronto Press Gayler, H.J. 1971. 'Private Residential Redevelopment in the Inner City (Vancouver),' Journal, Town Planning Institute, 57/1: 15-20 Goodall, B. 1972. The Economics of Urban Areas. London: Pergamon Hall, P. 1968. 'Land Use - The Spread of Towns Into the Country,' in M.E. Young, ed., Forecasting and the Social Sciences. London: Heinemann. Pp 95-117 Hall, P., et al. 1973. The Containment of Urban England. I: Urban and Metropolitan Growth Processes. London: Allen and Unwin Hoch, I. 1969. 'The Three Dimensional City,1 in H.S. Perloff, ed., Essays on the Quality of the Urban Environment. Baltimore: Johns Hopkins University Press for Resources for the Future, Inc. Hoyt, H. 1968. Urban Land Use Requirements 1968-2000: The Land Area Required for the Future Growth of the Urban Population of the United States. Washington: Homer Hoyt and Associates Lorimer, J. 1972. A Citizen's Guide to City Politics. Toronto: James Lewis and Samuel Maher, C.A., and Bourne, L.S. 1969. 'Land Use Structure and City Size.' Research Report 10. Centre for Urban and Community Studies, University of Toronto Manvel, A.D. 1968. 'Land Use in 106 Large Cities,1 in Three Land Research Studies. Report for National Commission on Urban Problems, Research Report 12. Washington Metropolitan Toronto Planning Board. 1970. Urban Form in the Toronto Region, 1995. Alternatives for Analysis. Metropolitan Plan Review Report 4

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Niedercorn, J.H.f and Hearle, E.F.R. 1963. Recent Land Use Trends in Forty-Eight Large American Cities. RM 3664-FF. Santa Monica: Rand Corporation Outdoor Recreation Resources Review Commission. 1962. Outdoor Recreation for America. Washington Pickard, J.P. 1967. Dimensions of Metropolitanism. Washington: Urban Land Institute Russwurm, L. 1970. Development of an Urban System Corridor: Toronto to Stratford Area 1941-1966. Toronto: Government of Ontario Simmons, J.W., and Bourne, L.S. 1972. 'Toronto: Focus of Growth and Change,1 in L. Gentilcore, ed., The Geography of Ontario. Toronto: University of Toronto Press Stamp, L.D. 1962. The Land of Britain: Its Uses and Misuse . London: Longmans White, O. 1969. Societal Determinants of Urban Form - Some Thoughts on the City in the Year 2000. Working Paper 45. London: Centre for Environmental Studies Whitehand, J.W.R. 1972. 'Building Cycles and the Spatial Pattern of Urban Growth,' Transactions, Institute of British Geographers. 56: 39-55

13 Urban transportation in the future ROSS D. MACKINNON Transportation in general and urban transportation in particular are subjects on which virtually everyone can express opinions - often very dogmatic ones at that. Like the weather, politics, and sex (not necessarily in that order), transportation is of vital concern to most people. It consumes a considerable amount of time, energy, and money for virtually everyone. Not only is transportation pervasive in that everyone is a consumer, but, because of its intermediate nature, the impacts of transportation go far beyond the immediate system user. In this paper transporation is discussed with particular emphasis on the possible future developments in urban transportation and their implications for urban activity patterns and the form of cities in Central Canada. First, the dimen-

Urban transportation in the future

237

sions of the current urban transportation problem are briefly outlined. Second, the role of transportation in shaping urban form is briefly discussed within theoretical, historical, and planning contexts. Third, the 'menu1 of future options in urban transportation is outlined - new conventional facilities, different planning and control procedures, as well as new modes. Finally some alternative future combinations of these options are identified and discussed with particular reference to large, medium, and small urban areas in Central Canada.1 DIMENSIONS OF THE URBAN TRANSPORTATION PROBLEM Transportation decisions are largely a response to current and sometimes anticipated problems. A definition of the current transportation problem is a natural starting point upon which to base speculations on future urban transportation developments. It is often emphasized that there is not a single transportation problem, but rather many problems. This apparently trivial statement is important to keep in mind, since it is unlikely that simple monolithic cure-alls such as more freeways or more rapid transit systems are very useful recommendations. Congestion Congestion is critical primarily during the morning and evening 'rush hours.' Routes leading to and from the core are most severely affected, although even in certain suburban industrial and commercial areas congestion levels are quite high for four hours every weekday. This problem is particularly visible in that commuters, knowing that millions of dollars are spent on improvements in urban transportation every year, see that travel times instead of declining are actually increasing. It should be noted that the commuter's analysis of the problem is not really complete. Even though trip times increase, the capacity of the system to transport vehicles, goods, and people has markedly increased. The availability of the improved transportation service (an increase in supply from SS to S'S1 in figure 13.1) has induced old users to use the system more frequently (now Qi trips per week instead of QQ trips). But more important, the increased supply has resulted in the shift of the demand curve (from DD to D'D') as new drivers use the system, shifting from

238

Urban futures for Central Canada

Figure 13.1 Demand and supply curves showing impact of new transport facility or facility improvement other modes or locating their residences to take advantage of the new facility. The new system carries Q2 trips per week at t2 minutes per trip instead of QQ trips per week at tQ minutes per trip. While travel times have increased, the amount of work done by the system has also increased. In an urban area which is growing rapidly it is often difficult to reduce overall travel times. Increased congestion does not necessarily mean that a transportation investment has been ineffective. It could be argued that popularity is in fact an index of success. In a no-growth context it is virtually certain that a transportation improvement will reduce congestion. Even if travellers are diverted to the improved facility, thus increasing travel times there, the routes which they previously used will be less congested and overall congestion levels would decline. In spite of these arguments it is likely that congestion will remain a critical urban transportation problem in the minds of most people, and many of the new developments in urban transportation will be introduced in an attempt to reduce congestion levels in response to a vocal commutersf lobby.

Urban transportation in the future

239

Although congestion is most severe during the morning and evening peaks, on many commercial streets it can be high for most of the day where trucks are loaded and unloaded. This has consequences for both goods and persons movement (Bates, 1970) . Accidents The destruction to life and property by transportation vehicles, primarily the automobile, has been of increasing concern to the public and elected officials. Most of these accidents take place within urban areas, and in the city most injuries are sustained by pedestrians. The effective separation of the motor vehicle from the pedestrian has been accomplished only on the urban expressway. For other reasons, however, there is a growing resistance to urban expressways. It is anticipated that more attention will be placed on pedestrian safety in the future. Thus far much of safety legislation passed and proposed has been directed towards driver and passenger safety, and this relates to moderateand high-speed travel. Pollution Transportation systems, with a few exceptions, characteristically emit pollutants of various forms - unpleasant fumes and noxious gases, solid particles (i.e., dirt), and noise. The growing concern for environmental quality has resulted in considerable criticism of the motor vehicle's role in urban environments. Certainly the internal combustion engine is the most important contributor of air pollution in urban areas. North American automobile manufacturers have been instructed to meet strict emission standards by 1975:. These cars will be more expensive and will perform less effectively than current models. A related problem is the current and projected 'energy crisis.1 Shortage of petroleum fuels will stimulate the research and development of efficient alternatives to the internal combustion engine and perhaps even new public modes of transportation. The cost of fuel and/or the capital costs of private transportation will increase relative to the price of other goods and services. 'All other things being equal,' these developments could reduce the rate of car ownership and usage in the city far below some of the more extreme forecasts (Sagasti and Ackoff, 1971) . It should be noted that the pollution consequences of transportation have both local and regional dimensions.

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The local aspect has been summarized frequently by the observation that no one wants 'an expressway in his backyard.1 The larger-scale impact has been widely recognized only recently. The emissions from motor vehicles can have regional, and perhaps even global, consequences. This view is partially responsible for the active search for viable alternatives to the automobile as the mode of urban transportation. Land consumption Except for residential uses, transportation and transportation-related uses constitute the most important land-use class in the city in terms of land area occupied. Between 35 and 50 per cent of the CBD of a large city is preempted by the automobile. Thus in areas where land values are highest transportation uses are dominant. There is a growing awareness on the part of city officials that a higher tax base would be possible if transportation land could be used for other purposes. More generally a relatively compact and therefore more easily serviced city would be possible;2 or alternatively, a city with larger lots and more recreational space, or a larger city with the same net density. This is not to say that the use of land by transportation is unproductive. But in areas with high land values there is obviously some incentive to look for modes of transportation which consume less land. There is a growing feeling that the motor vehicle, with its concomitant infrastructure of expressways, streets, and storage areas, is not a suitable means of transportation for the inner city. Neighbourhood effects In recent years many of the above complaints about the 'externalities ' of the transportation process have culminated in 'stop expressway' activities. Many neighbourhood groups, in particular, have viewed expressways as a threat to their community. The introduction of an expressway in an area may mean that some property in the community will be expropriated, displacing people in the community or important focal points such as a park or a tavern. In addition, residents fear that the expressway may generate traffic in the neighbourhood, thereby increasing noise, pollution, and accident levels. Finally a major linear facility of any type can act as a barrier to intracommunity movement, thus

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reducing the degree to which an area is in fact a community. These and other anti-expressway arguments were cited by the successful 'Stop Spadina1 group in Toronto (Gonen, 1970). Immobility of a large percentage of the population As the automobile's popularity and usage increased, the percentage of the population using public forms of transportation necessarily decreased. In areas where the density of population and automobile congestion are high, public transit service has been maintained and in some instances even improved. However in suburban areas, which were developed on the assumption that the dominant mode of transportation was to be the automobile, transit ridership remains low. In response to this low ridership transit authorities often cut back service and/or increase fares so that they can come close to covering their costs. These tactics, of course, reduce the patronage still further, and the cycle is repeated. The 'equilibrium state' of such a system is often very poor public transit service for certain areas of the city (and for entire small- to medium-sized cities). Non-drivers (the young, the very old, the physically handicapped, the poor, and those who simply have not acquiried the skill of driving a car, the latter group having a disproportionately large number of women), are severely penalized. They are limited in their ability to carry on an active and varied life, even to gain employment. One could argue that they should not locate their residences where public transit is inferior. Of course many - the young and those living in public housing, for example - have little choice in their place of residence. Others prefer living in the suburbs, but still feel that mobility is a public service which should be supplied to everyone. There is a growing dissatisfaction with this tyranny of the majority situation. THE ROLE OF TRANSPORTATION IN SHAPING URBAN FORM Theoretical and historical evidence Most of the economic theories of urban form postulate that the critical causal mechanism generating the spatial structure consists of a trade-off between residential location (defined as nearness to critical activity sites - places of work primarily) on the one hand and the location rent which must be paid on the other. Stated differently, the residential location process is assumed to be the result of a com-

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promise between lot size (or space consumption) and transportation costs. Assuming a city with a single employment centre, densities decline away from the centre as people sacrifice nearness to the job site in favour of larger lot size. Of course the nature of this trade-off process varies from one household to another, depending presumably on incomes and preferences. One of the implications of this fairly simple family of models is that overall decreases in transportation costs (e.g., by the introduction of a new mode of transport) result in an increase in the area of the city and a decline in net densities as people can locate at greater distances from the centre, without increasing transportation outlays. The empirical confirmation of this aspect of the theory is demonstrated by the contrasting structures of cities which developed in the nineteenth century and those developed in the twentieth century and even in the changing nature of development in older cities. The suburbanization process is largely attributed to the desire of many people, particularly those with children, to have more space than is economically possible in the inner city on the one hand, and to the increased accessibility of these areas with the advent of the automobile and highway systems on the other. Moses and Williamson (1967) express a different view. They claim that the suburbanization of residences, albeit on a somewhat restricted level was well underway before the automobile. It was in fact the truck which allowed the decentralization of employment, which, in turn, spurred on the suburbanization of residences. This alternative theoretical explanation of decentralization is rather difficult to verify empirically in that the automobile and the truck were introduced simultaneously; but it does indicate again the potential importance of transportation in shaping the form of the city. The theory of transportation-route impacts gives some insight into the critical role of transportation investments. Mohring and Harwitz (1962), Werner (1969), and Hartwick and Hartwick (1971), for example, demonstrate how land values may increase or decrease and the intensity of land use may change as a result of improving an old transport route or introducing a new one. These theoretical findings are certainly confirmed on a gross scale in an empirical historical context. In the urban expansion of the built-up area of Metropolitan Toronto

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during this century finger-like ridges of relatively highdensity development have grown out from the city centre, preceding by several years the urbanization within the relatively inaccessible interstitial areas. These corridors are related to major transportation facilities such as streetcar and electric interurban lines, railways, and major roads (see Hilton (1969), Kzanzberg (1970), and Mayer (1970) for a more complete discussion),. Overlaying these historical developments, the introduction of subway facilities in both Toronto and Montreal is creating new ridges of high accessibility and intensive land redevelopment, particularly in Toronto (see MacKinnon and Lau, 1973). There is ample empirical and theoretical evidence that the form of the city is in large degree the cumulative product of past and current transportation system configurations and technologies.3 Transportation planning Major developmental decisions regarding all large and pervasive systems are difficult. Often goals or objectives are imperfectly known or specified, and system impacts are construed narrowly by those making decisions. Frequently the implications, narrow and broad, of system decisions are imperfectly identified or understood. In the light of these general comments, let us turn to some specific examples. Virtually all of the demand for transportation is a derived or intermediate demand - a demand which originates from the desire to acquire other goods or services or engage in other activities. In general there is no intrinsic demand for transportation. In this sense transportation is a f bad f rather than a good. The transportation of commodities allows them to be sold and consumed, and others to be produced. Personal transportation allows people to undertake a rich variety of activities in different locations - working, shopping, visiting, 'recreating,' and so forth. It allows them to adopt certain life styles (e.g., suburban living, cottaging, 'jet-setting,1 etc.) which would otherwise be impossible or more difficult. An improved urban transportation system effectively expands the amount of land for urban uses and is thus a necessary, although not a sufficient, condition for urban growth. In spite of the general principle that improvements in urban transportation are made in order to increase the effective nearness of a wide variety of opportunities, most

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of the large components of our modern urban transportation system have been built for one purpose - to accommodate the home-work trip. The massive fleets of buses and streetcars, costly expressways and subways, and many arterials were initially justified to satisfy the large streams of morning and late afternoon migrants. Moreover on many routes this flow is directionally biased. Reduction of travel times or increases in capacity are generally spatially reflexive. That is, a facility built to make area A more accessible to location B usually makes B more accessible to A. Thus a freeway system built to service the residents of the suburbs by enabling them to live there and work in the inner city, also makes the suburbs more attractive to business and industry for two reasons: (1) residential-serving businesses move out to be close to their markets; (2) other businesses and industries can maintain close contacts with the inner city while taking advantage of lower land values, ease of land assembly, better intercity accessibility, and, at the same time be accessible to their employees. 4 Thus changes in the transportation system made to serve certain types of trips may have impacts on the location of other activities as these establishments attempt to utilize the inexpensive (virtually free) off-peak capacity. Industries and businesses move to suburban areas, reducing the relative importance of the core, whereas the initial impetus to build the facility was to serve the journey to core-area work places. Much of transportation planning has been based on the proposition that the pattern of land use, in large degree, determines what transportation system configuration is appropriate. Facilities were introduced that were thought appropriate for predicted land-use patterns. Such a strategy is undermined by the fact that the transportation system itself can affect the land-use pattern. If the relationship were perfectly symmetrical and reflexive, the initial prediction of land use will be reinforced. This would not necessarily be unfortunate if the predicted land-use pattern were desirable. Although there is in fact an element of the selffulfilling prophesy in transporation planning, we have already outlined an instance where unintended consequences may result from planning for a narrowly defined situation. Another example of unintended consequences has arisen within the context of limited-access highways which have been built

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to bypass large urban areas. The MacDonald-Cartier Freeway in Toronto is a perfect example of a freeway built to facilitate the movement of through traffic around the city but which in fact acted as a magnet attracting urban growth industries, businesses, and residences - thus making the transportation facility an urban rather than interurban facility. The 'normal1 growth of the city, in the absence of controls, would have surrounded the freeway in any case. The presence of the freeway, however, accelerated this envelopment and affected the form and probably even the magnitude of growth. This same freeway is having similar effects in shaping the growth of such smaller centres as London, Kitchener, and Kingston. Similarly, recreational routes Highway 400 and the Laurentian Autoroute north of Toronto and Montreal respectively have stimulated and reshaped industrial and residential development. To a considerable extent Barrie is now an integral part of the Metropolitan Toronto system. Not many, but significant numbers of workers commute from Barrie and points south to Toronto for work every day and periodically for shopping and entertainment. In other words, these transportation developments have not only affected the physical layout of the urban area, but also the way people use the existing physical structure - in particular, the development of a more extensive network of contacts. In summary, then, there is ample evidence that very few transportation facilities can have but a single purpose. In spite of the motivating basic problem (e.g., congestion during the morning and evening rush hours), transportation facilities will typically be used for other purposes (e.g., shopping, social and recreational trips, and commodity shipments) and thus will have consequences that were neither intended nor anticipated. FUTURE DEVELOPMENTS IN URBAN TRANSPORTATION:

SOME OPTIONS

In view of both the 'urban transportation problem1 and the role transportation obviously has had in shaping urban change, the future mix of transportation modes is a major topic of speculation among the general public, journalists, academics, and planners. Some of this speculation is in the tradition of science fiction.5 in recent years, however, there have been millions of dollars invested in studying the feasibility of innovations in urban transportation.

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It is tempting to look to new technologies for answers to our current problems; ultimately many such solutions will be adopted. These solutions, however, tend to require long lead times and substantial capital outlays; in addition, because they are new and unknown, they are characterized by a high degree of uncertainty - uncertainty with respect to development, production, and operating costs, as well as the degree of consumer acceptance and external consequences. For these reasons, then, in the discussion of future options we will first consider less radical breaks with the past: the phasing and location of essentially conventional facilities. Next the future innovations in transportation planning and control are outlined. Finally the likelihood of the emergence and widespread adoption of new technologies is discussed. New conventional facilities Without the introduction of radically new systems the form of a city could be substantially affected by changes in the existing system - increased spatial extent or quite marginal design standards in vehicles or routeways. For example, let us consider the critical decisions which will be made for the Toronto transportation system in the next few years decisions which could markedly affect the future form and even the magnitude of growth of the Toronto area. First, how much of the proposed expressway system will be implemented? Are there any likely additions or substitutions to these plans? Of the proposed expressway system, the Allen (or Spadina) Expressway has been halted by a decision of the provincial government; it is unlikely that it will ever be completed. Irrespective of this decision, it is virtually inconceivable that the cross-town or the Richview expressway will be completed. Of the proposed system, the only probable candidates within the city are the Scarborough expressway and an extention of Highway 400. These would provide the area with a virtually symmetrical system, thus encouraging a more or less compact urban form. Of these, the Scarborough expressway would have the first priority, although even that route is now in doubt. Other possibilities include the physical upgrading of existing arteries and restrictions on parking and cross-traffic during peak hours. A major freeway proposal in the Toronto area is a bypass (Highway 407) looping to the north, parallel to the MacDonaldCartier Freeway (Highway 401). Such a bypass, in the absence

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of restrictive controls on land-use development, will undoubtedly attract growth to the north of Toronto, a region supposedly to be retained as a low density greenbelt. In spite of this danger and the apparent difficulty in controlling land development, it is likely that such a facility will be necessary during the 1980s. The Don Valley Parkway is scheduled to be extended as a part of the provincial highway grid, but there are well-founded fears that this would exacerbate an already congested urban expressway. Finally the introduction of major activity centres often necessitates their servicing by transportation facilities. If, as seems likely, the Pickering airport is constructed, probably by 1980-2, it would be serviced by an expressway. Again, unless land use were severely controlled, such a facility would be used for other purposes and would stimulate residential and commercial development near the airport, thus interfering with the future expansion of this airport facility. A road built to serve a major traffic generator can have the effect of restricting the effectiveness with respect to that initial purpose.6 Of course the major debate on urban transportation is often between proponents of expressways and roads on the one hand and advocates of public transit on the other. There has been a general consumer resistance to public transit as shown by the large per capita decline in ridership in all metropolitan areas over the last twenty-five years - from 60 to 73 per cent in Central Canadian cities (Lea, 1967). In spite of recent major investments in rapid transit in Toronto and Montreal, total transit ridership is barely keeping pace with population growth. Many argue that more would use public transit if the service were more convenient, speedier, and more comfortable. Within the Toronto context again there is a strong likelihood that the subway system will be extended. It is virtually certain that the Spadina line will be built to serve the northwest sector of the city. It would, however, be difficult to justify any other major line in terms of current demand densities, although a Queen Street line, with a northern extension to the Danforth line and beyond, to serve high-density developments in Don Mills has some plausibility. In addition, of course, there would be some merit in attempting to structure land use and demand by introducing lines along Eglinton Avenue, for example. Such a line would serve the downtown area via connecting links with the Yonge and Spadina lines and would

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encourage the growth of an alternative high-density core at Eglinton and Yonge and a ridge of high density along Eglinton paralleling Bloor Street to the south. The increased costs of subway construction, however, makes such a decision unlikely. Other intensive modes of transit requiring less capital could have similar results. In addition to subways it is virtually certain that the network of commuter railway lines in Toronto will be extended to the north, northwest, and west, although this would seem to run counter to stated provincial government policy to limit growth to the north. Many people argue that improving the quality of service among existing 'collective1 modes of transportation is insufficient to attract increased ridership unless the effectiveness (or the cost) of the automobile is simultaneously reduced (increased). It is likely that this will occur in the near future. First, if expressway construction is (permanently) halted, then, with continued growth and concentration, large cities will experience increased congestion. This may induce drivers to use public transit if an attractive alternative is available. Second, on the legislative front North American automobile manufacturers are being required to reduce emissions and increase safety standards. This legislation should result in a costlier car a car which will be increasingly unwieldy in city traffic and not look or perform as well as current models. This could certainly result in the increased attractiveness of urban mass transit. Other means are suggested below. At odds with these regulations are the recommendations of some (e.g., Sagasti and Ackoff, 1971; Bieber, 1972) that urban automobiles should be much smaller to increase capacity of the system and decrease storage-space requirements. Bieber in particular suggests that a single automobile type can no longer serve in the dual role of inter- and intraurban vehicle. The ideal requirements for each role are to a large extent contradictory. Although subway developments in both Toronto and Montreal have been the most spectacular changes in transit since the war, most transit riders are still accommodated by the bus (arid, in Toronto, the streetcar) system. In most cases rapid transit is inappropriate, in that it requires large volumes of highly concentrated demand. Thus means to increase the effectiveness of bus transit should be seriously considered. One such method, easily implemented, restricts

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the use of one lane of an artery to buses only. An experiment with this method has recently been initiated along Eglinton Avenue in Toronto. Another variation allows buses to pass other buses as they are stopped in a bus bay at the curb for passengers. This allows each bus to stop at every second or third stop, thus closely simulating the performance characteristics of a rapid transit facility. Planning and control innovations The way in which the transporation-system hardware is managed is as important as the nature of the hardware itself. In this section we briefly review some of the current and likely future innovations irr software - how the transportation systemf s performance is controlled from hour to hour, day to day, etc., and how plans are formulated and implemented from year to year, and decade to decade. In the past ten years, with the widespread introduction of very high-speed computers and various types of remote sensing gadgetry, there has been a growing interest in management information systems - systems which give a decision-making agency relevant and timely information so that more effective decisions can be made. In a transportation context Metropolitan Toronto was one of the pioneers in developing an information system which has the capability to adjust the timing of traffic signals in response to changing patterns of congestion levels. It has been estimated that this development decreased arterial street trip times by some 9 per cent, in spite of a 10 per cent increase in traffic volume. Even more remarkable was the 73 per cent increase in trip times which occurred when the installation was shut down for a five-day period in 1967 (Hewton, 1969). Similar to this method is the metering of traffic coming onto an expressway in response to expressway traffic conditions. Another example is the proposal that signals be adjusted in a real time way so as to favour the movement of buses along an arterial. This is a special case of mode coordination. Keeping track of the status of various elements of different modal systems (location, speed, etc.) and identifying areas of actual and potential conflict Callow control of the total transportation system, so that capacity and efficiency are increased or certain desirable consequences are favoured. Introducing better methods for communicating relevant traffic information to the driver is perhaps the first step which might be taken towards developing

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automatic vehicle-control systems (Sagasti and Ackoff, 1971). Various policy instruments are available to modify transportation-system performance. Several planners and theoreticians have advocated the use of the market or pricing mechanism to change travel behaviour. This is suggested so that automobile users would be forced to pay the true congestion costs that they are imposing on the traffic system and the true costs of vehicle storage during the day. Pricing of system usage may be either through tolls paid as the facility is used or by a monthly or yearly licence to use the facility during peak hours. Similarly one could force parking rates to reflect the true opportunity cost of land. With both traffic- and parking-pricing strategies, the goal would be to limit automobile usage to those for whom it is the most valuable. This could have several effects. Presumably more people would take public transit in the short run. In the long run, however, more fundamental adjustments could take place. First, if a CBD location were essential for the place of work, workers would change their places of residences so that over time a denser distribution of population concentrated on transit corridors of high accessibility would result. Alternatively, if central locations were found to be less important, such pricing strategies could result in the acceleration of job suburbanization - suburbanization which would permit automobile drivers to use the (comparatively) uncongested highways in the suburbs. In a longer-term context it is likely that major metropolitan areas will set up comprehensive regional transportation-planning authorities to coordinate planning, monitoring, and control of transportation systems.7 These authorities will attempt to improve the efficiency of operation and development of the regional transportation system - in a narrow sense, the capability to move people and goods; and in a broad sense, to control the developmental and environmental impacts of the system. In particular it is very likely that acquisition of broad transportation corridors will be undertaken long before the need for the facility. This will not only reduce costs of improving the system but will also facilitate the orderly, coordinated development of land-use and transportation (and other utility) systems (see Lea, 1971, and First Conference of Canadian Mayors and Municipalities on Urban Transportation, 1969, for a discussion of this policy).

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New modes of urban transportation The final means by which urban transportation can be altered is the introduction of significantly new modes of movement. Speculation on these developments is perhaps the most difficult because of a large degree of uncertainty as to which options will be exercised and the sensitivity of the urban structure to each option. In view of these uncertainties, it is likely that we will see a proliferation of experimental demonstration projects relating to urban transportation (Science Council of Canada, 1971). These projects will vary from the relatively small-scale express bus lane experiments to the Government of Ontario commuter train projects already underway. Cities will become social laboratories which are frequently monitored, evaluated, and adjusted in response to information about on-going system performance. Experiments with new modes of urban transportation will be undertaken just as manufacturers currently test new market products. Of course the magnitude of many meaningful experiments with transportation systems may reduce feasible sample size and may in some cases significantly alter the structure of the subject - the city. Moreover in order to provide reliable results the new mode must be viewed as long-lived or permanent; otherwise one would not get a true picture of the implications of the adoption of the new technology. In view of these comments, it is possible that there will be some cities which have quite different means of urban transportation and with them different spatial forms and organization - some of which will in retrospect appear quite eccentric. Of course this will only happen if the anticipated experiments are bold, imaginative, and radically different one from the other.8 Different scales and conditions of movement necessitate different modes of transport. Bouladon (1967; 1969) and Bieber (1972) comment at some length on this observation. The automobile, for example, is not particularly effective for trips of less than half a mile; nor is it very effective for two- and three-mile trips if population and traffic densities are high. For longer trips of up to two hundred miles the automobile is unsurpassed under most conditions. On the basis of this simple observation, the continuum of urban transportation has been broken down quite arbitrarily into three spatial scales (Stanford Research Institute, 1968): major-activity-centre systems, local-area systems, and extended-area systems.

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Major-activity-centre systems are the simplest to deal with. They are concerned with moving people within areas of great concentrations of activity (CBDs, large shopping centres, airports, sports stadia, etc.). The new modes consist of either small capsules operating on their own guideways or a continuously moving belt (sidewalk). Already the latter type of facility has been installed in airports (Dorval in Montreal, for example) with considerable success. Terminal capacity and ease and speed of passenger movement have been considerably increased. Pedestrian malls would be obvious candidates for such facilities, and also connecting links between transportation terminals (Union Station and the subway in Toronto, for example). That these facilities will be introduced in Toronto, Montreal, and perhaps some of the smaller cities is virtually certain. As with all transportation improvements, this could have two consequences. First, movement within the existing activity centre would be easier and more pleasant. Second, and perhaps more likely, the activity centre itself could become considerably larger, thus dampening the effect on average trip time. In particular CBDs could become larger. In Toronto the already linear form of the CBD could be exaggerated. Airports, shopping centres, and sports and amusement complexes could become even more massive than they already are. Local-area travel refers to trips between 1 1/2 to 4 miles, and typically with spatially dispersed sets of origins and/or destinations. Such trips make up a fairly large proportion of suburban and medium- to small-city travel - trips to shopping centres, visits to relatives, friends, and local recreational areas, and feeder trips to commuter railways, rapid transit stations, and intercity transportation terminals. This is just the context in which automobiles perform best. This is one of the most difficult problems in developing new modes of transport - to provide competitive or superior service in situations which have emerged under the dominating influence of the automobile. New modes must attempt to defeat the automobile at its own 'game.' Because of this Lithwick (1970) takes a highly sceptical view of radical change: 'Because of our automobile-structured cities, the expectation is that no major transportation innovation will be feasible.' Although sharing some of this scepticism, one wonders if such a statement can be accepted at face value in view of the rapid adoption and remarkable influence of

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the automobile itself during this century.9 Of all the new modes suggested for such functions, the demand-activated bus system would seem to be most likely to be adopted. Several relatively small demonstration projects have been initiated in North America, one in Pickering township bordering Metropolitan Toronto on the east. With" such a system a fleet of small buses is dispatched in response to demands placed on the system. The passenger places a call from his origin, indicating his location and desired destination. The information on all such demands is analyzed by a decision-making unit (eventually a computer) and drivers are instructed as to their appropriate itineraries. The capability to make real time adjustment to incoming demands should exist. The result should be a system of small, quiet, non-polluting vehicles providing door-to-door service, thus approximating some of the service advantages of the automobile. The Pickering demonstration project, not computerized, is being carried out to act as a feeder to the GO commuter train project and is judged to be a success, although it is quite heavily subsidized (Bonsall, 1971). During off peak hours the system is made available for local area trips. Technologically it would certainly be possible to introduce widespread versions of a computer dispatched dial-a-bus system in Canadian cities within five to ten years. It is possible that the anticipated restrictions and standards to be placed on automobile design and usage will make these even more attractive. This mode does have the disadvantage that it is labour—intensive and will be subject to increases in costs due to higher wage rates. New technologies for extended area travel are perhaps the most difficult to forecast. In the Metropolitan Toronto and Region Transportation Study area the average trip length was 7.0 miles in 1964, and an increase to 8.0 miles has been forecast for 1980 as the urban area grows and distances become longer and non-CBD trips more important (Kates, Peat, and Marwick, 1967). Trip patterns of this length are of two types - highdensity concentrations of both origins and destinations, or low-density concentrations at either origins or destinations. With high-density origins and destinations rapid transit modes can be extremely effective movers of people. If such a city form is desirable, or acceptable, improved fixedroute rapid transit technologies with their own guideways

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could be developed and introduced. The city could then take on a form not dissimilar from the star-shaped nineteenthcentury city, with high concentrations of people along transit routes or pockets of development around stations, with invervening open space. However without rigidly enforced zoning such a form would be considerably dampened by the availability of automobile or feeder (demand-activated) bus service. In an attempt to develop a compromise solution the Ontario government plans to experiment with an intermediate-capacity rapid transit system. Operating above ground, but on its own right-of-way, the service characteristics of this system are similar to the subway, while lower capital costs make operation feasible in residential areas of intermediate density. An extensive network of routes is planned with the first being completed by the late 1970s (see Davis, 1972). More radical changes for these sorts of trips include various dual-mode proposals. These systems combine the privacy and door-to-door convenience of the automobile with the high-speed trunk-line performance characteristics of rapid transit. Using this mode a vehicle can be manually operated on city streets to provide local access to origin and destination. In addition, however, it can be incorporated into an automatically operated transit system for most of its journey, thus decreasing travel times and/or increasing system capacity. Full-scale implementation of this mode would take between 20 and 25 years and would entail considerable development, production, and operation costs. Some means of gradual transition to this system would have to be developed. Compatibility between the conventional private automobile and the system would be necessary. Of all the future intraurban transportation systems considered here, this one is perhaps the least likely in view of the questions of costs and compatibility. However in terms of performance characteristics it most closely approximates the advantages of both automobile and rapid transit. In terms of consequences its acceptance would permit the continued low-density expansion of the urbanized area without even necessitating the relative decline of the CBD. Only with this mode is a centralized commercial structure of a very large urbanized area compatible with a low-density form of residential development. Non-transportation developments In addition to changes in transportation technologies, it is probable that modifications in related systems will have

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impacts on transportation and the urban system of which it is a part. Perhaps most intriguing of all these possibilities is the emergence of much improved electronic communications systems (Dakin, 1972). The possibility exists to substitute information transmission for physical movement of people. The direct effects of such a substitution would be very small - fewer interoffice business trips. However, if offices are located in the CBD to facilitate these contacts, then the offices would no longer be tied to the core - offices could suburbanize, thus reducing central-city congestion and journey-to-work travel times and eliminating the need for costly rapid transit systems and radial expressways (Harkness, 1972) . Although this 'scenario1 is plausible, it is certainly not inevitable. As the Science Council (1971) states, 'There is no necessary direct link between a decreasing need for travel and the actual amount of travel.' This will happen only if improved electronic communication is viewed by the users (i.e., business executives) as an effective substitute for face-to-face contact. There is little evidence either to support or to refute this hypothesis. Some point to the fact that historically the introduction of the telephone has resulted in, or rather been accompanied by, a phenomenal increase in the volume of travel, thus suggesting that the two modes of interaction, far from being substitutes, complement and reinforce one another. On the other hand, one can point to the suburbanization of many offices and the form of such cities as Los Angeles: certainly such developments would not have been possible without improved communications technologies. Similarly, with the widespread adoption of television fewer trips of a social and recreational nature are made than would otherwise be the case (Hilton, 1969). Another example of a non-transportation change which could have profound implications for the transportation system is modification of the normal work schedule. Some staggering of work hours is widely used in many large cities. Some government employees in Toronto begin work at 8:30 am and leave at 4:30 pm; others have later hours; and still others have flexible schedules. These practices essentially increase the effective capacity of the existing street and transit systems to handle the large numbers of office workers entering the core area by spreading the demand over a longer time period. One should expect more of this practice and increased coordination, although a decrease in effectiveness

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may result when the working hours of the offices do not coincide. Peterson (1971) discusses the implications of a related innovation - a shorter work week. He estimates that, if demand is distributed over time by the introduction of a four-day work week, transportation demand on any one day could be reduced by some 40 per cent! With increased worker productivity as a result of automation, it is likely that the number of working hours will be reduced from the current standard 40 hours per week. How the new total is distributed over the week will have important consequences for transportation. If the number of working days per week is reduced to four or three days, the reductions in demand outlined by Peterson would result. Similarly, if the five-day week were retained but holiday periods lengthened, there would be decreases in demands. Of course, it is possible, even probable, that if traffic congestion were lessened, the physical extent of the urban area would, in the absence of governmental controls, increase as people choose to maintain (rather than reduce) travel times so that they can gain larger lot size and improved environmental amenities. AN OVERVIEW OF FUTURE URBAN TRANSPORTATION IN CENTRAL CANADA In the preceding section options ranging from simple extensions of existing systems to radically new innovations have been outlined. It should be noted that the entire list of options is certainly much longer than those discussed here only those which appear to be most likely have been included. In this final section educated guesses are made about the nature of future transportation systems within the contexts of three (somewhat arbitrary) city sizes: very large urban metropolises (Montreal and Toronto); large urban areas (e.g., Ottawa, London, Quebec City, etc.); and smaller urban centres of less than 100,000 population (e.g., Kingston, Sarnia, Trois Rivieres). Future transportation in small urban centres Although not as spectacular as those in the larger cities, the transportation problems of small urban areas are often quite severe. They are, of course, of a different type. Whereas congestion could be cited as the most critical problem in large cities, lack of service of a particular type

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would be most important for small centres. With the rapid increase in automobile ownership and improvements in the street system, together with the decreasing densities of population and the suburbanization of some functions, the revenue earned by transit systems in small urban areas has often been insufficient to pay operating expenses for many routes, even entire systems. Declining revenues, as we have seen, result in a cut-back in service, which in turn results in reduced patronage, and so on. Sometimes this spiral is halted with subsidies; sometimes it stops at some low level of services; sometimes service is withdrawn completely. 10 Such cutbacks in service effectively disenfranchise those who do not have access to an automobile. Although many of these smaller cities will increase dramatically in size over the next thirty years, it is unlikely that their growth will be of a type to make conventional modes of rapid transit effective options. Some form of demand-responsive bus system may be appropriate in these contexts. One could certainly anticipate an intensive program of experimentation with such a system for at least one city of this size. With this system adopted, one would expect the city in question to be larger and have a slightly higher residential density than otherwise would be the case. Other than this, it is unlikely that any other dramatic changes will occur in cities of this size. In all likelihood the dominance of the automobile will increase and the poor public transit service will be simply one of the known costs of living in small urban areas. Future transportation in large urban areas Currently these areas have moderate levels of traffic congestion and lower public transit ridership than larger cities. As these cities grow, one should expect both these variables to increase. It is likely that some efforts will be adopted to increase public transit ridership, but, except in larger cities of this class, these efforts will meet with only limited success. It is possible that some intermediate-capacity rapid transit systems could be introduced in such cities as Ottawa, Quebec City, and Hamilton. The Ottawa-Hull metropolitan area would be particularly appropriate because of its anticipated rapid and sustained growth (to a population of over one million by 2000), and because of the likelihood that the National Capital Region will be used as a showcase for

258

Urban futures for Central Canada

improved public transport systems supported by federal grants.11 Future transportation in large metropolitan areas There are really only two urban areas in Central Canada of a truly metropolitan stature, Toronto and Montreal. Only these areas have mass rapid transit facilities, commuter rail systems, and anything approaching a well-developed network of expressways. Only in these centres is there a varied mix of both transportation problems and possible solutions; it is in these places that most major transportation innovations are likely to occur. The following summarizes some of the more probable developments in these areas: 1 One should expect a decline in the rate of construction of new urban expressways. There is a growing, and nontransitory, sentiment that expressways consume too much space and cause too much congestion and pollution to be effective modes of intracity transportation. They are particularly inept means of providing accessibility to the core area. Figure 13.2 shows the remarkable contradiction of the area accessible (within 30 minutes) to the Toronto core from 1964 to 1969 - this in spite of several millions of dollars of investment over the period. In Montreal, although opposition to expressways is increasing (Beauregard, 1972a), it appears likely that expressway construction will continue for a longer time than in Toronto. 2 It is improbable, after currently proposed extensions to the existing network are completed or rejected (Spadina or Bathurst and Queen Streets), that other new subway lines will be constructed in Toronto. Intermediate rapid transit facilities are favoured by the government, and an extensive network based on such a system is planned, the first line to be operational by the late 1970s. Rapid transit lines encouraging the development of alternative urban cores could be anticipated. Rapid transit plans for Montreal are quite ambitious (Beauregard, 1972b). Some 20 additional miles of subway lines are planned to open in 1976. Most of these additions are extensions of existing core-oriented lines to the northeast, northwest, and southwest of the CBD. 3 In the inner city the private automobile will become less important, both relatively and absolutely. One can extra-

Urban transportation in the future

259

Figure 13.2 Thirty-minute auto-peak hour isoline to GBD for Metropolitan Toronto, 1964 and 1969 polate from the experience of large North American cities such as New York and Chicago, where private cars are far less important than taxis, buses, subways and trucks. One can also anticipate the introduction of an improved bus transit system of the demand-activated type in suburban areas. Suburban transportation is likely to be far different from that in the inner city. In the former, a decline in the importance of the private automobile should be anticipated, whereas in the newer low-density areas the automobile is likely to dominate for some time to come. 4 Innumerable combinations of technological options are available to improve urban transportation. It is likely that less spectacular developments in the way such systems are managed will be at least as important as 'hardware ' improvements. For example, one should expect many 'software1 innovations to be introduced to divert more people from the automobile mode in the inner city. Pricing and other regulations are relatively inexpensive to initiate, although often difficult politically. 5 Because of limited space and information this paper has emphasized the movement of people, to the virtual exclusion

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Urban futures for Central Canada

of goods transportation. This is unfortunate because goods movement is a vital part of every urban transportation system (Highway Research Board, 1971; Bates, 1970).12 Moreover much of the off-peak traffic congestion results from the movement, loading, and unloading of trucks. In the future one should expect significant changes in truck and terminal design and fleet management procedures. In particular terminal consolidation, in part related to the widespread adoption of containerization should occur, resulting in a strong focusing of movements of large trucks in a few suburban locations. Experiments with other forms of goods movements - pipelines and conveyors for solids should also be anticipated as an attempt to dampen the growth of truck-generated congestion. 6 As Bourne and Harper indicate in paper 12, one can already observe the emergence of many focal points in large urban areas. To the extent that much of the future growth of employment will take place at locations other than the CBD, many facets of the current urban transportation problem may not be of importance in the long run. The demand for urban transportation is currently much more spatially diffused than it once was. Kates, Peak, and Marwick (1967), with specific reference to Metropolitan Toronto, forecast a 55 per cent increase in peak hour travel by 1980, only a small proportion of which will consist of increases to the CBD. In addition to a greater spatial diffusion one might also expect a relatively less peaked temporal distribution as well. This paper has sought to summarize some of the basic elements of the massive literature on future urban transportation systems. An attempt has been made to relate this literature to the specific context of cities in Central Canada. Only speculative, judgmental forecasts have been made, but, where possible, these have been rationalized in the light of past experience and current theory. The form and life style of Canadian cities 30 years from now will depend to a considerable extent upon what transportation decisions are made during the next five to ten years. This paper has sought to identify the most likely options and to consider the spatial implications of adopting alternative courses of action.

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NOTES 1

Many of the same topics are discussed with reference to all of Canada in Parkinson (1971). For more numerical and technical details the reader is referred to this excellent review. 2 Of interest in this context is the recent highly speculative and revolutionary proposals of Dantzig and Saaty (1973) on the 'Compact City.1 3 In addition one could certainly argue that the overall rate of growth of a city is a function of the ease of movement within the city. This is difficult to substantiate empirically, however, for two reasons: (1) there is often not much variation between the transportation systems of cities of the same size and economic status; (2) large, congested cities have tended to grow more steadily than smaller centres. Thus it would appear that external economies of scale more than offset high congestion levels. In spite of these empirical observations, ceterus paribus, one would still expect a city with a more effective transportation system to attract more economic activity and people than other cities. 4 In many cities, notably those which developed as ports, relocation from the core may in fact be a move towards the centre of the population distribution. In Toronto, for example, because of its truncation by Lake Ontario the CBD is far removed from the centre of population. Thus Eglinton and Yonge is by most measures more accessible than Queen and Yonge (MacKinnon and Lau, 1973). In this context a simple but rather important observation can be noted: waterfront cities have significantly longer trip lengths to the CBD than cities of the same size whose growth is unobstructed by these large physical barriers. This can have two implications: first, insofar as transportation costs to the core are important considerations, growth could be impeded or could occur at higher densities than would otherwise be the case; second, the addition of 'central1 facilities could take on a different form, tending to decentralize more than in other cities. 5 It can be noted in passing that these writers have not been far wrong in their visions of interplanetary travel. It is also remarkable that such fantastic advances have been made in long-distance travel over the past 40 years, while intraurban transportation technology has changed only marginally by comparison.

262 6

7

8

9

10

11

12

Urban futures for Central Canada

Stone (1971) and others argue that these are some of the reasons why fixed-route rapid transit systems, with few if any intermediate stations, are to be preferred over conventional expressway facilities. Recently the Metropolitan Toronto Transportation Plan Review has been set up to examine transportation planning in Metropolitan Toronto. It is anticipated that one of its recommendations will be the setting up of a permanent transportation-planning authority. There are several reviews of future technological possibilities in urban transportation. Among the most accessible and useful are Richards (1966), Stanford Research Institute (1968), Housing and Urban Development (1968), Irwin (1968), Hutchinson (1970), and Burco and Henderson (1971). A recent survey of Canadian municipal leaders would give some support to Lithwick's view. Few if any expressed the expectation that new technologies would solve their problems. New freeways and arteries, street widening, more effective traffic control procedures, and, for larger cities, improved public transit facilities were given high priorities (Kates, Peat, and Marwick, 1970). Such drastic measures have been taken far more often in the United States than in Canada. In the United States cities of up to 100,000 have had transit services withdrawn. In Canada public transit has enjoyed better service and consumer acceptance even in smaller cities. Although much larger, Washington, DC, would probably not have planned as elaborate a future rapid transit system were it not for its status as the federal capital. Bates (1970) estimates that from 1/4 to 1/3 of vehicular traffic in cities consists of truck movements, and Lea (1971) estimates that truck transport accounts for some 40 per cent of urban transport costs in Canadian cities.

REFERENCES Bates, M.V. 1970. Goods Movement by Truck in the Central Area of Selected Canadian Cities. Prepared for Canadian Trucking Association, Ottawa Beauregard, L. 1972a. 'The Automobile and Its Impact on Montreal,1 in Montreal Field Guide. 22nd International Geographical Congress, University of Montreal. Pp 170-8 Beauregard, L. 1972b. 'Public Transport in Montreal,1 in

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263

Montreal Field Guide. 22nd International Geographical Congress, University of Montreal. Pp 179-88 Bieber, A. 1972. 'Should We Urbanize the Motor Vehicle?1 Transportation, 1: 79-95 Bonsall, J.A. 1971. 'Dial-A-Bus: The Bay Ridges Experiment. ' Department of Transportation and Communication, Ontario Bouladon, G. 1967. 'The Transport Gaps,' Science Journal, vol. 3 Bouladon, G. 1970. 'Technological Forecasting Applied to Transport,' Futures, 2: 15-23 Burco, R.A., and C.D. Henderson. 1971. 'Systems Innovations for Urban Transportation,' Transportation Engineering ASCE, 97/TE2: 205-26 Dakin, A.J. 1972. Telecommunications in the Urban and Regional Planning Process. Toronto: University of Toronto Press Dantzig, G.B., and Saaty, T.L. 1973. Compact City. San Francisco: Freeman Davis, W.G. 1972. 'An Urban Transportation Policy for Ontario.' Toronto, Ontario First Conference of Canadian Mayors and Municipalities. 1969. Background Papers and Proceedings of Conference held in Toronto. January 1969. Gonen, A. 1970. 'The Spadina Expressway in Toronto - Decision and Opposition.' Discussion Paper 5. Philadelphia: Research on Conflict in Locational Decisions, Regional Science Department Harkness, R.C. 1972. 'Communications Substitutes for Intra-Urban Travel,' Transportation Engineering Journal ASCE, 98/TE3: 585-98 Hartwick, P.G., and Hartwick, J.M. 1971. 'An Analysis of an Urban Thoroughfare.' Working Paper A.71.3. Ministry of State for Urban Affairs, Ottawa Hewton, J.T. 1969. 'Metropolitan Toronto Traffic Surveillance and Control System,' Civil Engineering, 39/2: 40-5 Highway Research Board. 1971. Urban Commodity Flow. Special Report 120. Washington Hilton, G.W. 1969. 'Transport Technology and the Urban Pattern,' Journal of Contemporary History, 4: 123-35 Housing and Urban Development. 1968. Tomorrow's Transportation. Washington: HUD Hutchinson, B.G. 'A Summary of Urban Transport Technological Innovations,' Proceedings, Australian Road Research

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Board, 3/2: 283-301 Irwin, N.A. 1969. 'Public Transit and the Quality of Urban Living,1 Study Papers. First Canadian Urban Transportation Conference, Canadian Federation of Mayors and Municipalities. Pp 91-185 Kates, Peat, Marwick and Co. 1967. A Forecast of the 1980 Travel Demand in Metropolitan Toronto and Surrounding Region for the 7-9 A.M. Period. Prepared for MTARTS, Toronto Kranzberg, M. 1970. 'The Social Impact of Transportation Technology: Some Lessons of History,1 in G. Smerk, ed., Essays on Transportation Problems in the 1970s. Bureau of Business Research, Indiana University, Bloomington. Pp 4-35 Lea, N.D., and Associates. 1967. Urban Transportation Developments in Eleven Canadian Metropolitan Areas. Prepared for the Transportation Planning Committee of the Canadian Good Roads Association Lea, N.D., and Associates. 1971. An Evaluation of Urban Transport Efficiency in Canada. Prepared for the Ministry of Transport, Government of Canada, Ottawa Lithwick, H. 1970. Urban Canada: Problems and Prospects. Ottawa: Central Mortgage and Housing Corporation McDaniel, D.E. 1972. 'Transportation Forecasting: A Review,' Technological Forecasting and Social Change, 367-89 MacKinnon, R.D., and Lau, R. 1973. 'Measuring Accessibility Change,1 in L.S. Bourne, R.D. MacKinnon, and J.W. Simmons, eds, The Form of Cities in Central Canada. Toronto: University of Toronto Press Mayer, H.M. 1968. 'Emerging Technological Developments in Urban Transportation and Their Relation to the Form of the City.' Study in New Systems of Urban Transportation. II: A Collection of Papers. Barton-Aschman Associates, Inc. Pp 223-44 Metropolitan Toronto Transportation Plan Review. 1972, 1973. Reports. Toronto, Ontario Mohring, H., and Harwitz, M. 1962. Highway Benefits: An Analytical Framework. Evanston, 111.: Northwestern University Press Moses, L.N., and Williamson, H.W. 1967. 'Location of Economic Activities Within Cities,' American Economic Review, 57: 211-22 Parkinson, T.D. 1971. Passenger Transport in Canadian

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Urban Areas. Research Publication 9. Ottawa: Canadian Transport Commission Peterson, N.W. 1971. 'New Transportation Concepts for Urban Growth and Control.' SP-3636. System Development Corporation, Santa Monica, California Reynolds, D.J. 1971. The Urban Transport Problem. Research Monograph 3. Urban Canada: Problems and Prospects. Ottawa: CMHC Richards, B. 1966. New Movement in Cities. London: Studio Vista Richards, B. 1969. 'Urban Transportation and City Form,' Futures, 1: 225-39 Sagasti, F., and Ackoff, R.L. 1971. 'Possible and Likely Futures of Urban Transportation,' Socio-Economic Planning Sciences, 5: 413-28 Science Council of Canada. 1971. Cities for Tomorrow: Some Applications of Science and Technology to Urban Development. Report 14. Ottawa: Information Canada Stanford Research Institute. 1968. Future Urban Transportation Systems: Descriptions, Evaluations and Programs; Impacts on Urban Life and Form. Final Report (2 vols) prepared for US Department of Housing and Urban Development, Washington Stone, T.R. 1971. Beyond the Automobile: Reshaping the Transportation Environment. Englewood Cliffs, NJ: Prentice-Hall Werner, C. 1970. 'Formal Problems of Transportation Impact Research,' Annals of Regional Science, 4: 134-50

14 Household movement trends and social change JAMES W. SIMMONS

Discussions of future urban form stress the significance of the evolution of preferences and behaviour patterns among urban households in determining future urban landscapes. As incomes increase, child-bearing declines; or as ethnic and religious differences become blurred, the desired urban environment is altered. One research approach based on this

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premise evaluates the preferences of existing urban households (Lansing, 1966; Butler, et al., 1969) to see how different kinds of households trade off access against cost, housing quality, or amenity. An alternative strategy, described below, describes changes in aggregate patterns of residential movement over time. When matrices of households movements within Metropolitan Toronto are examined at different periods in the recent past several themes emerge. The transience of these patterns is clearly evident; there is a lack of predictive power by simple models; and the dominance of new housing opportunities in structuring the patterns is shown. These findings do not necessarily lead to improved urban forecasts but they clarify some of the issued involved. RECENT TRENDS The data The Metropolitan Toronto and Region Transportation Study Home Interviews (1964) provide the bulk of the data for the analysis. The main features of the information are described elsewhere (Hill, 1973; Simmons, 1973a). These data include 3.3 per cent of the households of Metropolitan Toronto, each of which was asked where it last resided and when it last moved, in addition to a battery of questions about the nature of the household and its travel patterns. Since only information about the most recent household move is recorded, there are some difficulties in creating a time series of flow patterns. Although the sample represents all households, any sorting out by time of move also differentiates households by other characteristics. Those households that have moved during the last year are predominantly young, renting households. Those that moved during 1950-4, and have not moved since, are most likely to be middle-aged, larger households now living in their own home. The farther back in time the analysis goes, the smaller the proportion of actual moves in that period that are retained, and (probably) the less representative the observed movement patterns. The overall movement pattern for the six-year period 1958-63 among the 18 zones of analysis is presented in Figure 14.1. Four main streams of movement are visible: to the east (zones 7, 8, 6, 5); to the north (10, 11, 9, 3); to the northwest (13, 14, 15, 2); and to the west (13, 16,

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267

Figure 14.1 Total household flows, F, 1958-63 18). The flow pattern is not symmetrical - it shows the influence of the rapid outward growth of the city during this time period. The patterns Despite the limitations of the sample at different points in time, the patterns are both consistent and instructive. The maps (figure 14.2) identify the stability of the period before 1949 when the depression and the war essentially froze the housing stock. There are high rates of withinzone flows (table 14.1) and close linkages among all zones. The next ten to fifteen years, however, feature a remarkable shift; strong outward movements are spurred on by the massive construction of new single-family dwellings - the suburban boom. The pattern continues in the late fifties, but becomes focused in particular growth zones (6 and 18). Towards the early sixties a kind of stability is restored, and the parameters of symmetry and trace begin to increase again (table 14.1). (Alternatively the sample begins to pick up a wider cross-section of moves). By 1963 the bulk of the suburban growth has begun to move beyond the Metro boundary. Note that the concentration of both origins and destinations apparently declines over time since the study area is a closed system (Metro) which has slowly built out-

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Urban futures for Central Canada

before 1944

1949-54 Figure 14.2 Variations in flows by time of move ward from a single concentrated core area. The implications of this sequence are many. It is obvious that stability of flow patterns is very unlikely in a rapidly growing city, unless the analysis is limited to zones built up at the initial time period. New housing biases the

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269

1960

1963

flows strongly. Second, the shift of flows to a sequence of destination zones can be observed; e.g., the major flows from zone 7 are first internal, then to zones 8, 6, and 5 in that order. On the other hand, the relations among zones 13, 14, 15, and 18 appear to be quite stable.

TABLE 14.1 Flow matrix parameters:

Sample size Trace (%) Origin concentration Destination concentration Symmetry (r)

Time of move

1963

1962

1961

1960

58-60

56-8

54-6

49-54

44-9

Pre-44

1958-63

46063 39.9

40056 40.6

34466 38.1

29617 36.6

52707 30.7

40501 30.3

37175 29.3

49666 32.8

18064 43.6

24311 50.2

203,409 36.9

0.346

0.385

0.410

0.405

0.446

0.478

0.505

0.560

0.583

0.652

0.390

0.336 0.266

0.347 0.275

0.343 0.248

0.267 0.175

0.342 0.071

0.346 0.357 0.031 -0.009

0.371 0.053

0.516 0.353

0.645 0.410

0.308 0.263

Household movement trends

271

The maps also complement the findings by Murdie (1969) on the factorial ecology of Toronto in 1951 and 1961, by showing how the patterns of residential segregation become stronger over time. In the early time periods one can observe a considerable interaction among sectors with strong links, e.g., among zones 14, 10, and 7. Even the early suburbanization trend reveals widespread source areas for each growth zone. By 1960, however, the migration streams have become well-defined channels - blue-collar, upper middle class, Italian blue-collar, and so on. During the decade residents (and/or real estate agents) began to identify more clearly that various different sectors of the city were more or less suitable for different life styles. It is possible to analyze the flow matrices which generated these maps in order to evaluate the significance of the differences among them. Results published elsewhere (Simmons, 1973a) indicate that the assumption of stationarity, of similar likelihoods of movement over time, does not hold for periods longer than one or two years in Metropolitan Toronto. As the study period is lengthened, the patterns are more and more dissimilar. It appears that forecasting household movements on the basis of the migration patterns observed here must be undertaken very cautiously indeed. As a description of the process of social change in Toronto, the transition matrix is a very transient indicator. Growth is too rapid and too specific in location. The degree of bias introduced by the particular characteristics of the data set is not altogether clear, but the underrepresentation of the frequent moves made by transient households probably reduces observed movement near the city core - the most stable pattern. Descriptive models With the transience of the movement matrices clearly established the analysis now seeks out the source of the instability. A series of regression models were undertaken which attempted to allocate between zone moves for the matrix of moves in the period 1958 to 1963. The independent variable is the value of f-[j, and the dependent variables include

the number of moves generated in the origin zone,

the number of moves ending in the destination zone, the

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Urban futures for Central Canada

straight line distance between i and j, denoted as d^,-, and the number of social trips observed between i and j, . S1.1' Knowledge of the amount of movement at origins and destinations is of considerable importance at this scale of analysis, since there is a great deal of variation in zone size.

(Parentheses indicate standard error of regression coefficient. ) The distance variable makes the model more effective, adding about 20 per cent more explanation. There is a problem in defining a value of distance for da. Some experimentation indicated that, by making da greater than 1.0, the contribution of the distance variable could be improved (at the expense of the social-trips measure) and part of the overprediction of within-zone moves eliminated. If da - 4.0 (for all zones), then

This compares to a distance regression coefficient of -0.717, and R? = 0.540 for d±± = 1 . 0 . The contribution of the social trips measure is very small:

When the residuals from the final model are mapped the familiar pattern (figure 14.3) emerges. The model as formulated cannot adequately predict the wi thin-zone move'rs because of the distance assumption noted above, nor can it anticipate the strong sectoral outward flows from the older areas to the new suburbs, even though the actual increment

Household movement trends TABLE 14.2 Correlations among regression variables for migrant flows

Correlations (FC1) ( n = 324)

1

1 Flows (f )

1.000

2 Origins (T f . . )

0.409

1.000

3 Destinations (I, .f . .)

0.416

0.002

1.000

-0.549

-0.156

-0.108

0.572

0.277

0.324

4 Distance (i, j) 5 Social trips (i , j)

2

3

4

273

(18 zones)

5

1.000 -0.513 1.000

of housing opportunities is incorporated in the equation. The latter represent new linkages which are being added to the social structure of the city, and the existing socialtrip pattern is an inadequate predictor. Apparently permanent (long-run) moves lead short-run contact patterns.

Figure 14.3 Residuals from the flow model The pattern of residuals does reveal some barriers to movements in addition to the tendency to move outward rather

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Urban futures for Central Canada

than inward. The Don River, separating the 'East End1 from the north sector is significant in the older parts of the city, and an invisible culture barrier separates the north sector (predominantly WASP) from the northwest (largely Italian). The barriers and unspecified biases appear to be less powerful in the suburban areas, although this may be entirely the result of size variations in the zones. It is apparent, even for a given time period with a set of large areal units, and row and column totals given, that movement pattern cannot easily be described. The sources of error are mainly conjectural: 1 A considerable random error exists due to the sampling error. The 5700 household movements are used to create 324 flow dyads and many estimates of f^j are based only on a handful of families. 2 The addition of new housing units in limited numbers of locations superimposes fundamentally different patterns of movements on those already generated by the existing housing. These new housing patterns also change rapidly over time. 3 The flow patterns are also modified by the evolving social characteristics of neighbourhoods. Movements between any area i and any other area j are actually aggregates of migration streams of many different kinds, each of which responds to social characteristics at the origin and destination. TOWARDS THE FUTURE From these investigations of recent trends, and drawing on additional analyses of household migration (Simmons 1973a), it is possible to suggest how the relocation process itself is changing and where it is going, and to comment on the implications for future urban form. Although few comparable studies have been undertaken for other cities, the results of Greer-Wootten and Marshall (1972) for Montreal do not contradict the findings here. It can be assumed that the same general pattern holds for all of the larger Canadian cities. The Relocation Process For any single time period the movement pattern is extremely complex. It contains a very large amount of information, but, as shown above, the structure is not easily summarized.

Household movement trends

275

The earlier flows in this period are largely symmetrical, and are only modestly responsive to the friction of distance. The migration streams are usually biased towards peripheral locations, but there are always significant counter streams; and, although a very crude regionalization of flows can be identified (Simmons, 1973a), there are observable migration streams between all locations in the metropolitan area. A continual conceptual difficulty is the need to differentiate the moving population from the population as a whole. The great variation in age-specific mobility rates means that a sample of moves for any time period is predominantly composed of young households, and overrepresents their preferences and spatial biases. The further implication is that the resultant effect of these movements may be quite slight, since many of them may promptly move again in the next time period. People who have moved recently are much more likely to move in the near future. Historical evidence (Simmons, 1968) implies that mobility rates will not change to any great extent. The only important cause of change is the demographic structure. If the rate of growth of Canadian cities slackens, the amount of internal movement may also decline slightly. Distance and spatial pattern were surprisingly ineffective as determinants of aggregate movement patterns. In Toronto the asymmetry of recent movement weakens the distance bias. The location of particular opportunities can be an effective predictor of movements, but it is difficult to specify appropriately for disaggregated households. Two kinds of reality about urban space must be faced: first, not distance, but concentration of relevant opportunities within space (and time) governs interactions; and, second, there is a great inhomogeneity of activities (households and others) within spatial areas. The results of these complexities are the inhomogeneity of migration streams and the diversity of destinations from any one origin zone. Study of the relocation process is further complicated by the transience of the movement pattern. The spatial concentrations of new housing in the urban area modify the distribution of available opportunities in each time period, but even the older parts of the city generate significantly different origin and destination fields over time as the composition of households in these neighbourhoods changes. The longer the period studied, the fuzzier the picture of a rapidly evolving process; the shorter the time period, the less relevant the picture to notions of social change.

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Urban futures for Central Canada

The movement patterns described for Metropolitan Toronto are undoubtedly influenced by the rapid rate of growth of the city during the study period. During the six-year period of study about 102,000 new housing units were completed in Metro, an increment amounting to 24 per cent of the 1961 housing stock. During the same period of time this study identified 203,000 household movements within Toronto, not all of which created vacancies, because of new family formation and undoubling. In addition, many (uncounted) repeated moves took place during the study period, but the vacancies and opportunities created approximately cancel out. The implication is that new housing played a very important role in the pattern of residential movement, accounting for one-third to one-half of the observed move destinations. In terms of the movement pattern the impact is even greater because of the extremely uneven distribution of new housing opportunities on the periphery and in a few areas of apartment expansion. A very large proportion of movement destinations are concentrated in a small number of zones. Moreover, since the period of rapid growth of a particular area is brief in a rapidly growing city, the pattern of new housing shifts rapidly from year to year. The supply of new housing in Toronto during the study period was largely of two types: single-family dwellings (about 36 per cent) and high-rise apartments (55 to 60 per cent). These housing types perform very different roles in the movement process. New houses attract families at a very mobile stage and essentially freeze them in that dwelling. The probability of out-movement becomes sharply reduced. In-migrants to new single-family dwellings come mainly from other dwellings in the Toronto area, rather than from out-of-town locations or by means of new family formation. New apartments, on the other hand, attract highly mobile people who remain highly mobile. Informal studies of new high-rise apartments indicate out-movement rates of up to 70 per cent per year. Apartments attract new families and in-movers from other parts of Canada. Movers to new apartments create a much smaller number of vacancies in Toronto than movers to the same number of new houses, but they will generate far more future movers. Accompanying the spatial sequence of new housing is an extremely regular evolution of the spatial distribution of demographic characteristics (Murdie, 1969; and, in particular,

Household movement trends

277

Simmons, 1973b). A tremendous surge of young people, aged 15-25, moving into the core area is followed by a vigorous out-migration into the suburbs of these same young people in the next decade. The evidence for all age groups describes a highly integrated demographic system driven largely by the continuing net migration of young people into the metropolitan area. The changing residential structure The significance of intraurban migration in the understanding of future social change within neighbourhoods has been a fundamental premise underlying this study. It seems clear that net change in an area can only be discussed as the residual of two relatively independent processes - in-movement and out-movement. The results, however, have not been very satisfactory. The movement processes themselves are very complex and not easily reproduced, and depend in turn on the evolving spatio-temporal pattern of residential land use. And the new housing market, as is frequently stated (e.g., Grigsby, 1963; White, 1971), is modified only in very indirect fashion by the characteristics of demand. What does seem clear is the dominance of the twin forces of urban growth and the life-cycle sequence, which lead to other kinds of social change almost incidentally. Although the significant role of ethnicity in Toronto could not be investigated in this study, it was possible to gain some ideas of the trends in social-class shifts (see Simmons, 1973a). The starting point in a discussion of changing social patterns is the assumption of identifiable social groups for study, which have differing locational preferences - defined by the need for access to the city as a whole or to their own cultural and institutional activities or to housing requirements. Social change is defined as the modification of the map of these characteristics; it can occur through changes at the national level, by the growth of a city, or by relative changes within the city. The social pattern of a city which is not undergoing rapid growth or extensive migration exchanges with the outside will still evolve. Households are continuously shifting from one life-cycle group to another, and new households are being created while others break up. Similarly the process of social mobility may alter the status of a family which remains in situ. Life-cycle stages, new household formation, and rates of economic change - particularly when defined by

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income level - reflect national trends in fertility, marriage, and increases in real income. The high rate of depopulation among large parts of the older area of Toronto as young households leave is primarily the result of the rise in income levels, which permits young people to leave home for an apartment, and then move to a suburban area for child-rearing without having to double up with their in-laws. A related source of social change is the relative increase or decrease in the numbers of certain social groups by migration or differential rates of increase. Toronto has been characterized by increases in the proportions of residents with Italian and other Mediterranean origins, and young people. As a result areas inhabited by the growing groups expand (Murdie, 1969), with the direction of expansion determined by market forces of relative ability to pay by different groups. If the city is not growing, these changes take place within the existing stock, but in Toronto much of the expansion of ethnic and social-class groups has taken place at the periphery because of the rapid rate of growth of the entire urban area. The main source of change in social patterns in Toronto is the continuing high rate of net migration of young households to the core of the city, which creates a series of waves of life-cycle shifts outward from the city centre. The pattern of net migration by age groups is now well defined (Simmons, 1973b) with very regular distributions, varying strongly for different age groups. The main zones of life-cycle change are as follows: the expansion of the young in-migrant areas in the core area as apartments are built; the aging and undoubling of households in the older residential areas (essentially those areas built more than ten years before); and the rapid in-movement of all age groups - but particularly young families - into the areas of rapid growth at the periphery. If the Toronto metropolitan area continues to grow as anticipated, the general pattern of movement should persist well into the future. The strongest recent trend is a shift in new construction from single-family to multi-family units, but the location and, presumably, the social characteristics of families in town-houses or condominiums are much like those of home-buyers a decade ago. If anything, the movement pattern should be more stable in future decades, since the new developments of this type are usually found in the interstices of the recent suburbs rather than in completely

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undeveloped areas. They also tend to be more socially heterogeneous than a neighbourhood of new single-family dwellings. The dominant influence of forces of urban growth and the life cycle leads to the lack of symmetry in the movement matrices and the rather low degree of within-zone movement. Other forms of social change follow more or less as a consequence. It was pointed out in an earlier paper (Simmons, 1973a) how difficult it is to identify areas of rapidly changing social-class characteristics - at least at the level of analysis used in this study. The most obvious patterns are the further sorting out of existing social-class patterns, with blue-collar residents tending to move out of the middleand upper-class sectors. The contention here is that the growth of the various social classes has been largely accommodated by the spatial extension of their long-established residential sectors. The filtering down of housing takes place largely within the blue-collar sectors, where there is a clear economic gradation from older areas to newer. The social-class characteristics of suburban residents in all sectors are quite similar - the range, for example, between the $30,000 and $50,000 new home (as of 1972). Actual transitions of areas within the city from one social class to another are very limited and appear largely related to local adjustments which strengthen the sectoral pattern, such as the extensive renovation ('white paint and wrought iron1) of small streets of poor housing in the North Yonge sectors; or the insertion of 'young professional1 apartments in similar areas. The overall theme of this paper is the close relationship between the movement pattern of households and the evolving distribution of housing opportunities. In particular, it must be stressed again how difficult it is to understand the movement of a group of households from any one area or from any one type and cost of housing, of all which are open to them. The spatial pattern of residential moves is very much a by-product of the housing market. Policy possibilities It appears that the potential of the residential relocation process as a vehicle for carrying out urban policy depends in turn on the ability to manipulate the supply and demand sides of the housing market. Recently there has been a rapid

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increase in research into the nature of the housing industry (Smith, 1971; Chamberlain, 1971) on the supply side, although as yet no one has really put together the entire process for a single metropolitan area. It does appear that manipulation of the type and location of new housing could effectively alter social patterns in Toronto, easily overriding any biases in the housing selection procedure itself. People are not locked into neighbourhoods. The major uncertainties about the future lie in the prediction of housing demand. There is a need to monitor the process of household formation continuously,- to build demographic models, to examine the relation between housing costs and the number of non-family households, and to inquire into the preference structure of households of all kinds. How do households trade off housing alternatives? The residential relocation process is viewed as a matchingup of households and opportunities. The process will change in the future only insofar as the incomes and characteristics of households change or as the amount and cost of available accommodation are altered. There is no apparent formal spatial structure in.the movement process itself which permits extrapolation to future points in time. REFERENCES Butler, E.R., et al. 1969. Moving Behavior and Residential Choice: A National Survey. National Co-operative Highway Research Program, Report 81. Washington: Highway Research Board Chamberlain, S.B. 1971. Land Development and Urban Planning: A Study of Developer Behaviour in the Toronto Area. Unpublished MSc thesis, London School of Economics and Political Science Greer-Wootten, B., and Marshall, J. 1972. "The Urban System,1 in L. Beauregard, ed., Montreal Field Guide. Montreal: Les Presses de 1'Universite de Montreal Grigsby, W.G. 1963. Housing Markets and Public Policy. Philadelphia: University of Pennsylvania Press Hill, F.I. 1973. 'Migration in the Toronto-Centred Region,1 in L.S. Bourne, et al., eds, The Form of Central Cities in Central Canada: Selected Papers. Toronto: University of Toronto Press Lansing, J.B. 1966. Residential Location and Urban Mobility: The Second Wave of Interviews. Ann Arbor: Survey

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Research Center, Institute for Social Research, University of Michigan Murdie, R.A. 1969. Factorial Ecology of Metropolitan Toronto, 1951-1961. Chicago: University of Chicago, Department of Geography, Research Paper 116 Simmons, J.W. 1968. 'Changing Residence in the City: A Review of Intraurban Mobility,' Geographical Review, 58: 622-51 Simmons, J.W. 1973a. 'Household Movement Patterns,1 in L.S. Bourne, et al., eds, The Form of Cities in Central Canada: Selected Papers. Toronto: University of Toronto Press Simmons, J.W. 1973b. "Net Migration Patterns,1 in L.S. Bourne, et al., eds, The Form of Cities in Central Canada: Selected Papers. Toronto: University of Toronto Press Smith, L.B. 1971. Housing in Canada: Market Structure and Policy Performance. Ottawa: Central Mortgage and Housing Corporation

15 The city in the periphery GERALD HODGE Our politics and our sciences of urban areas are, with few exceptions, characterized by two biases. On the one hand, they are generally centralist in nature: they feature the 'core,1 the 'central city,' and even the 'suburbs.' They are inward-looking, as revealed by such epithets as 'urban sprawl1 and 'scatteration,' as conceived in those models which are concerned with such variables as 'distance to the CBD,' and as seen in most of our metropolitan transportation plans which want 'to get people downtown.' On the other hand, they also maintain the distinction between urban and rural areas, i.e., the existence of an urban-rural continuum. Somewhere just beyond the limits of the built-up city, it is presumed, one can find a rural character to the settlement, the employment, and the life style of the residents. However our urban politics and our urban sciences tend to avoid the implications of the drift of populations and

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activities to the urban periphery which has occurred in all large North American cities in the past 25 years. The various trends are well known. For more and more people the exodus to outlying areas in search of space and privacy for residences has increased with expanded automobile ownership and income. And, as people move outward, so do retail and service establishments. Industrial plants are no longer tied to central locations for transportation and marketing reasons and can take advantage of the larger sites usually available in the periphery. Increases in leisure time and income in recent decades have raised both the aspirations and actual demands of city dwellers for recreation opportunities and vacation homes, both permanent and mobile. While our major cities have experienced large-scale growth, this growth has been accompanied by development over increasingly wider areas. The changing scale of urban development around Toronto, for instance, may be grasped from the following figures. The city of Toronto and the older suburban towns, all largely built up by 1940, encompass much less than 100 square miles. When metropolitan government was undertaken in the mid-1950s, it was deemed necessary to allow 230 square miles for future development and just over 700 square miles for planning control. The Metropolitan Toronto and Region Transportation Study of the mid-1960s felt that 3,200 square miles more adequately covered the urbanizing area. And the Toronto-Centred Region Plan of 1970 encompassed 8,600 square miles. If the area of interaction of urban dwellers with vacation cottages is used as the measure, over 15,000 square miles around Toronto is being 'urbanized.1 Urban forms of settlement and urban life styles, the two sides of urbanization, now permeate the periphery of all large cities in North America: Toronto and Montreal are no exceptions. The increased scale of urban territory and influence revealed in the above trends carries with it the impression of central-city residents participating in activities over a much expanded space. It also suggests new urban communities growing up in what is often, disparagingly, called fthe fringe,1 certainly not just a direct extension of the regional 'core.' There are already over 160,000 people living in a zone that is between 15 and 40 miles from the city of Toronto. Twice that many are expected to live there within three more decades, according to the province's Toronto-Centred Region Plan. Over 300,000 people live in a zone that is between 40

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and 80 miles from Toronto, excluding those in the KitchenerGuelph-Brantford urban areas. This zone is expected to accommodate 500,000 new residents outside its major cities. The majority of the present residents as well as those who will come to live in the area 15 to 80 miles outward from Toronto are urban people. They pursue urban activities and seek urban employment; in generaly they follow urban life styles. There now exists, in the region around Toronto, not just a simple outward extension of city development but rather a web of urban settlements and urban activities. It is not a continuous built-up area but rather an area which contains a variety of urban living environments and considerable open space. THE CONCEPT OF AN URBAN FIELD Friedmann and Miller (1965) formulated the concept of 'the urban field1 to explain the increased scale of urban life such as is occurring around Toronto. Their idea was 'to emphasize the diminishing centrality' (of the metropolitan area) and the crisscross pattern of interactions which occur in a large metropolis, although these relate ultimately to the original centre which gave rise to the urban field, as Friedmann was to say a few years later. He goes on: ... we have, in effect, the same range and diversity of life styles and living patterns as we have in the old central cities, but now over a much larger area leading to different kinds of communities, different kinds of community perceptions, different types of social behaviour. And all of this gives rise to new kinds of problems with which we are really not yet very well acquainted. (Colloquium on the Toronto Urban Field, 1970) The urban-field concept allows us to deal with the diffusion of urban environments and urban behaviour occurring in the region around Toronto. It recognizes that there is, in effect, a city in the periphery - not a single city, but rather a set of urban elements related to one another as well as to the central city. Together these elements compromise a more or less continuous web, or field, of urban activities and attitudes. The furthest extent of this field cannot be precisely demarcated for Toronto; suffice it to say that at 25-30 miles beyond the edge of the present built-

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up city there is still a strong urban bias to life styles and environments. The existence of an urban field, therefore, argues against an urban-rural dichotomy between the developed city and the surrounding space. It also argues that it is necessary to view the urbanized area and its problems from the vantage point of the periphery rather than just to look outwards from the core. STUDIES OF THE TORONTO URBAN FIELD Beginning in 1967 a series of probes into the nature and extent of the Toronto urban field were undertaken: studies of people and communities in the periphery, of residential patterns, of industrial development, of rural land subdivision, and of cottaging and recreation activities. The approaches were sometimes deductive, sometimes inductive, but there was one constant: the acceptance of a study space defined by a 100-mile radius from Toronto. This space was assumed to be large enough to contain the basic features of an urban field. The sections to follow summarize the results of these probes into the periphery of the Toronto region: who lives there, how is the space used, what are the attendant problems? Living areas in the periphery The periphery of the Toronto region was settled for agricultural purposes over 125 years ago. Since that time, and increasingly in recent decades, many farms have been abandoned because of the poor quality of the soil. The towns of the region grew up as agricultural service centres. Many, such as Barrie, Orangeville, Guelph, and Lindsay, developed non-agricultural industries and grew in population as farmers left the land and migrants came from other places. Another form of non-farm habitat found in the periphery is the singlefamily home on a relatively large piece of land (often ten acres or more). These three year-round habitats - the farmstead, the town, and the non-farm isolated residence - are found today throughout the periphery. The latter two are experiencing growth; the producing farmsteads are declining, but are not about to die out. There is a fourth type of habitat in the periphery, the vacation cottage, of which more will be said later. In demographic terms the typical picture painted for rural

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regions is a lack of population growth and considerable outmigration. Even for peripheral areas around large cities the picture is one of the metropolis draining off the rural population. For the Toronto urban field just the reverse is true. Within a radius of 50 miles from Toronto most urban centres and townships have shown continuous population growth over the past 40 years. In the decade from 1951 to 1961 the rate of increase was over 30 per cent for all but a few townships, and the population of none declined. This trend continued in the 1960s. In a study of migration flows in southern Ontario for 1951-61 both Rodd (1967) and Koop (1967) found inflows of population to almost all parts of the area within 80 miles of Toronto. Only a few urban centres failed to experience positive migration rates. The same was true for townships, with the inflow being almost entirely 'rural non-farm1 population moving to small centres or dispersing throughout the countryside. A detailed study of a sector of the urban field approximately two townships wide and extending over 100 miles directly north of Toronto confirmed the presence of a quickly urbanizing periphery (Heaps, 1968). By borrowing the method of gradients from Bogue's (1949) classic study of metropolitan dominance evidence was sought for changes in the slope of the gradients along the sector for several demographic variables. The tendency for the slope to become less steep as the distances from Toronto increased was interpreted as indicating a growing spread of urbanization. For example, one tends to expect rural population density to be higher near the edge of the metropolis as a result of more intense farming and/or greater non-farm density, and then to taper off as low-density rural activities come to predominate. It was found that not only had the average rural population density nearly doubled in the ten years, but that it had also increased much faster from 40 to 80 miles away than it had for townships much closer to Toronto. The rural population gradient had all but disappeared by 1961. Three other gradients examined also proved insignificant. Rural non-farm population, which one associates with the urbanization of rural areas, was not found in 1951-61 to be increasing any faster near the metropolis than 80 miles away. Neither the rate of overall rural population growth nor the rate of in-migration for rural townships was found to be higher closer to the metropolitan area. It was concluded that the field of interaction previously contained in Metro-

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politan Toronto and its immediate environs widened considerably between 1951 and 1961. Another probe describes the farmland fractioning process that gives rise to the land holdings which become the habitat for many 'rural non-farm1 families (Kusner, 1968). A study of 16 townships north and east of Toronto found large land holdings being broken into 10-acre and 25-acre parcels such that the new plots accounted for as much as 15 per cent of the non-publicly-owned land in some townships. These plots were termed 'Non-Urban/Non-Farm1 (NU/NF) because they were neither related to intensive farming nor associated with an extension of local urban centres in the study area. Of the townships examined the median proportion of land so subdivided was just over 8 per cent; the median number of NU/NF plots was just over 300 per township. Other evidence indicated that this NU/NF process is most prevalent in the zone 15-50 miles from Toronto. Using the median number of NU/NF separations (300) and applying it to the number of townships within this zone (40) suggests a market of about 12,000 such properties covering between 120,000 and 300,000 acres of the urban field. Although most of these NU/NF plots do not have permanent residences on them (only about 10 per cent do), field observations indicate that this is not likely to remain the case for much longer. Provincial government regulations, in effect since 1969, restrict extensive land separation of this type, but already up to 500 square miles of the urban field has been alienated in this way. Under present constraints it could accommodate only about 12,000 families, many only on a part-time basis. Most of the people who have gone to live in the periphery of the urban field are to be found in typically urban subdivisions of modest homes that have been built in and around the many small towns. In what was once the purview of the well-to-do and mobile 'exurbanite,f these subdivisions are to be found 40 miles and more away from downtown Toronto. In the period 1950-68 just over 17,000 acres (about 27 square miles) were included in approved subdivisions within about 40 miles of downtown Toronto (excluding the lakeshore area). Four-fifths of this total were in subdivisions adjacent to, or near, existing towns. Most of the 'commutershed' population of the province's Toronto-Centred Region Plan live in such subdivisions. Four towns which have received considerable subdivision activity — Acton, Georgetown, Kleinberg, and Orangeville —

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were probed to examine the kinds of people who live in peripheral subdivisions, their attitudes, and their activity patterns. Of the families interviewed the following profile emerges: the median income is $8,000-10,000 per year; the median level of attainment is high school graduation; the median number of children per family is two; over half of all husbands are employed in professional or managerial occupations; all own their own homes; nearly 30 per cent own two cars. When these families were asked why they had chosen a peripheral location, the predominant answer was either that it was 'close to the country1 or that it was faway from the city1 while the house they chose attracted them mainly because of its 'low price' (relative to the metropolitan area). A total of two-thirds of the families studies lived previously in the Toronto region; 40 per cent moved from the metropolitan area to the peripheral town.l Activity patterns were examined in order to find the structure of life spaces participated in by families who chose to live beyond the metropolitan area. The following features summarize their life spaces: 1

place of work is usually outside the local community but within 20-40 minutes travel (by car) from home; 2 shopping is mostly done in the local community, for both day-to-day purchases and shopping goods, except furniture purchases from the metropolitan area; 3 most health services are obtained in the local community, except specialist medical services from the metropolitan area; 4 recreation activities in a variety of locations, but mostly within 20 minutes of home; 5 socializing (visits to friends and relatives) takes place over considerable trip times, with the median one-way trip being 45 minutes; and 6 larger nearby towns play an important role in supplying goods and services not obtainable locally. The picture presented above contradicts a widely held view (mainly by those who live in the central city) that families who go to live in peripheral subdivisions simply extend their linkages outward from the metropolitan core. Rather the process seems to be one of rendering a whole new life space emanating from the new residence covering the local centre and other nearby towns and reestablishing a few

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shopping and socializing links back into the metropolitan area. Indeed their patterns of activities are not that much different from their central city 'cousins,1 except in reverse. They live in an urban milieu with its own spatial situation. Their perceptions of the city are different from those who live at or near the core; the problems they face are different. One must go to the 'outside and look inwards' to appreciate fully the peripheral living area. Travel patterns in the periphery There is a substantial fund of information about the travel patterns of people living in the Toronto urban field beyond the metropolitan boundaries contained in the Metropolitan Toronto and Region Transportation Study of 1964 (MTARTS). This data source was used to test several hypotheses about the 'urbanness' of residents of the periphery (Gravel, 1968). The MTARTS arrayed its data in a series of roughly concentric zones around Toronto. The most distant zone was called the 'outer rural ring' and covered the area from 20 to 45 miles outwards. It contained 37,000 households at the time of the study; car ownership was the same as for the suburban boroughs of North York and Scarborough, and the income level was the same as areas closer in, such as East York. The rate of travel (trips per capita) for residents of the urban field increases with the distance of the zone from downtown Toronto when all trips are taken into account. The corollary is that the lower the density of population the greater the number of trips a person is likely to make, because, it can be assumed, facilities and establishments are more dispersed in low-density areas. The same profile does not emerge for average trips to work: the highest rates are in the inner and outer suburban zones around Toronto. The outer rural ring shows a lower average work-trips-per-capita than for the central city. The explanation may lie in a lower labour force participation rate for women in the periphery. It might be expected that average trip time per capita would be longer for persons in low-density areas of the urban field. In the outer rural ring, however, average trip-time-per-capita for all types of trips is virtually the same as for suburban zones. For home-to-work trips alone the average trip-time-per-capita is least on the periphery because of the relative closeness of jobs and/or the higher average speeds possible on less congested country

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roads. The average duration of home-to-work trips of outerrural-ring residents is 26 minutes, compared to 28 minutes for the region in aggregate and 30 minutes for suburban areas. Trip duration is distributed differently for the outer rural ring than for other zones in the field. Using 18minute intervals, the profile for the periphery shows two peaks; in the 0- to 18-minute interval and in the 54- to 72-minute interval. Residents of the outer zone are able to complete nearly half of their trips in less than 18 minutes, a substantially greater proportion than in other zones. But the residents of the outer zone also have a significant proportion of trips, about 10 per cent, which require 54 to 72 minutes to complete. The spatial distribution of trips by residents of the periphery has several interesting aspects. First, the outer rural ring retains more of its trips within its boundaries than any of the other zones, nearly 57 per cent. Second, most of the remaining trips are shared by the four inner zones in decreasing proportion toward the core zone. Third, trips originating in the outer rural ring have a greater affinity for centres or rural areas within the zone than they have for the metropolitan area or nearby cities. These findings confirm the impression gained in the study of peripheral subdivisions. Despite their urban behaviour and preferences for urban habitats, people in the periphery are not dominated by links to the older metropolitan area. Industrial patterns in the urban field There is a well-established location pattern of industrial plants in the Toronto urban field which is characterized by a core and several radial corridors. Just over 43 per cent of manufacturing firms in the region were located within Metropolitan Toronto in 1966. An additional 43 per cent were in urban centres situated along four highway-railway corridors extending west, east, north, and southwest from Toronto. Only 13 per cent of all plants were located in the remainder of the urban field. A further perspective on this skewed distribution shows that, when counted by municipal area, the core and corridors account for only 25 per cent of the land area of the urban field (but include most of the population). Among the corridors the distribution was as follows in 1966: the Lakeshore West (Mississauga to Hamilton) contained one-fifth of all plants; the 401 West (Guelph to London)

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nearly one-sixth; the Niagara (Hamilton to Welland) 4 per cent; the Lakeshore East (Ajax to Belleville) 4 per cent; and the Yonge North (Metropolitan Toronto to Barrie) also 4 per cent. With regard to types of industries, most have the same general 'core and corridors1 distribution when viewed by two-digit SIC categories. Only 7 of the 20 groups have a distribution that is significantly different. Food products industries are found widely distributed throughout the urban field, as are printing and publishing firms. Lumber and wood products are found skewed toward the northwest quadrant of the field, along with the furniture industry. Leather products plants are concentrated west of Toronto, while plants producing electrical machinery and those in the miscellaneous industries group are mostly located in the largest cities of the urban field. The 1966 pattern of manufacturing plants just described was a slightly modified version of the pattern of five years earlier. First, 7300 plants in 1966 represented an increase of more than 700 over the 1961 level, or a 10.7 per cent increase. Second, the highest rate of growth of new plants in this period was in areas beyond the core and corridors, thus leading to greater dispersion of plants in the urban field. Third, the corridor to the east of Toronto, which had not previously grown very fast, expanded its number of plants 70 per cent faster than the region as a whole. And fourth, the Yonge North and 401 West corridors also grew substantially faster than other areas. Although there is an indication of a modest dispersion of plants toward the peripheral parts of the urban field in the 1961-6 period, the preponderance of new plants, nearly 80 per cent, continued to locate in the core and along the corridors, despite the high-cost characteristics of the latter locations. Ontario's Equalization of Industrial Opportunities program, in operation since 1967, has been particularly effective in a zone 50-100 miles around Toronto in encouraging new firms. It has had its strongest impact in communities along the lakeshore east of Toronto (Dawes, 1972). The obvious predilection of manufacturing plants to locate in and around major cities and along major intercity transportation corridors may not, however, greatly affect residential development in the urban field. For, even if the home-to-work trip parameter of 30 minutes continues to con-

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strain residential location, it can be shown that an area of approximately 10,000 square miles would be within easy commuting distance of industries locating within the various corridors.2 This amount of space could accommodate up to 20 times the present population. The pattern of industrial plants offers many options for regional development. Second homes in the periphery About one family in seven in Metropolitan Toronto owns a vacation cottage,generally within a range of 50 to 150 miles from the city (Wolfe, 1965; Ontario Department of Tourism and Information, 1971). This represents about one-third of a million metropolitan residents; many more thousands rent cottages. The vacation cottage is more properly called a 'second home,' as it is in the 1971 Census of Canada. Metropolitan Toronto residents spend an average of 3.3 weeks vacation there each year, as well as an average of 14 other weekends from May to October. Over 60 per cent of Toronto cottageowners use their cottages for varying periods during the winter also (Ontario Department of Tourism and Information, 1971). Thus, on the average, Toronto residents establish their households in their second home for about one-sixth of each year. The incidence of second homes grew by 2.5 times in the 17 years from 1950-67. The growth rate was a steady 4 per cent through the 1960s. Nearly one-half of Ontario cottages have been built in the last ten years. Forecasts made by the Ontario government are for a further expansion of second homes by a factor of 1.8 from 1966 to 1986 (Ontario Department of Municipal Affairs, 1969). That portion of the Toronto urban field with the greatest incidence of second homes is generally to the north and northeast of the city. Over 90 per cent are found in the Muskoka-Haliburton-Georgian Bay North area (33.9 per cent), the Lake Simcoe-Georgian Bay South area (37.2 per cent), and the Kawartha Lakes area (19.8 per cent). These sectors range from 50 miles to 170 miles outwards and cover about 15,000 square miles. Several factors account for this 'recreation field1 pattern. To the west the natural-resources endowment is not as conducive to water-oriented outdoor recreation, and, although accessibility and natural-resources endowment is good to the east, there are competing streams of traffic from urban centres in eastern Ontario and the United States.

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Two probes into the vacation-home phenomenon provide some insights into (1) the structure and behaviour of cottaging and (2) the impact of second homes on peripheral areas. The first provides a profile of cottagers obtained from personal interviews. Cottagers tend to have incomes higher than the provincial average of over $10,000 per year, usually own detached homes in the city, and have a family size larger than average. Nearly half of the cottaging families have a second or third car. The average length of journey to the second home is 135 miles; the average trip time is 2.8 hours, and the trip is invariably made by automobile. Most cottagers have used, and in most cases owned, the same cottage for more than ten years. Beyond knowing who the cottagers are and where they cottage, it is useful to know something of their activity patterns once they are ensconced in their second homes. In general, cottagers have a well-developed set of links to a community of interest in an area up to 15 miles around their second home. Between two and five miles is the most common range for travel to shopping and automobile service facilities. Movies and medical services are obtained at greater distances. Sixty per cent of cottagers patronize more than one urban centre for shopping. Cottagers often visit one another at distances of 10 to 20 miles and more. Weekly trips for shopping, automobile services, and the like are the general pattern. Trips for visiting are usually not made oftener than once per month. When asked the extent of their community of interest, one-half think of it as within five miles, and one-quarter think of it being 30 to 50 miles outwards from their second home. Cottagers whose second home is accessible by road (in contrast to those which can be reached only by boat) are reasonably mobile. The enlarged life space of cottagers evidenced by these activity patterns and mobility has a direct impact on the economic structure of urban centres in the periphery (Hammer, 1968). A correlation between population size and the number of retail and service functions for centres in cottage areas and for other rural centres, shows that urban centres within the 'recreation field1 have a significantly higher number of retail and service establishments than non-resort centres of the same population size. Most centres in the 'recreation field1 experienced either growth or stability in both population and numbers of functions in the period 1961-6. In contrast, few non-resort area centres in eastern Ontario

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grew in either population or numbers of functions. These findings bear out one of Friedmann and Miller's (1965) original contentions about the urban field: the flow of urbanites to the periphery will have a beneficial effect on the economy of otherwise depressed areas. Second homes also affect the local governments of the periphery. The new cottages may not be a blessing to these municipalities, many of which have meagre resources. The majority of townships in the study area have enacted subdivision-control bylaws in response to pressures for cottage development. These controls indicate the lands suitable for development and the standards for lot size, access roads, and sanitary services. The latter is particularly important in the portion of the recreation field which lies on the Canadian Shield with its shallow soils and rock underlay. Zoning bylaws were enacted for most of the townships too. In an increasing number of bylaws not only are cottagedevelopment areas delineated, but the period of occupancy is also specified. Cottage occupancy is often prohibited over the winter from December to May when the dwelling is not of 'permanent1 construction because the demands for snowploughing, road maintenance, and protective and health services for dispersed population in the winter months could put considerable strains on local finances. But the trend to 'winterized1 cottages is also growing, thereby undermining the intent of such controls.

The new mobility and the periphery Urban residents not only transfer their households to the periphery; they increasingly exploit the open-space resources with a wide array of vehicles for personal physical mobility. The boat, increasingly motorized, is the most familiar vehicle: 81 per cent of Ontario cottagers own one or more boats, representing about one-third of a million boats. Fast coming to rival the boat in popularity is the snowmobile (Perry, 1970). From less than 10,000 machines in use in Ontario in 1965, the numbers grew to 170,000 by 1971, and that figure is expected to double by 1975. About 25 per cent of cottage-owners currently own a snowmobile (Ontario Department of Tourism and Information, 1971). To these two widely used vehicles one must now add an increasing array of others, some old and receiving renewed interest, like motorcycles, and some new such as hovercraft. Trail bikes (miniature motorcycles), go-carts, ATVs (all-

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terrain vehicles), dune buggies, hydrofoils, and personal jet packs give an idea of the extent of vehicles on the market or soon to be marketed. The internal combustion engine, reduced in size and complexity, is the great catalyst in allowing increased physical mobility (Kumagai, 1970). Yet another facet is the rapid growth in vacation vehicles which can be used as a 'temporary residence.1 The general categories are pick-up campers, travel trailers, tent trailers, and motor homes, but they come in a bewildering variety of sizes and shapes. Sales and rentals of vacation vehicles have been growing by about 20 per cent per year in recent years. The spatial accessibility permitted with these vehicles is unnerving. Given seven different types of terrain, from lakes through rough land to snow, at least three different vehicles are available for use on each type of terrain. Few parts of the urban field are now inaccessible, and indeed as much as 95 per cent of the North American continent is accessible with vehicles available today. Combine the possibility of mobility with the low cost of these vehicles, and it is little wonder that their use is so widespread. With the exception of pick-up campers and motor homes, the cost of most recreation vehicles is between one-sixth and onethird of the cost of a family automobile. It is now possible, using a combination of these vehicles, to be fully mobile in all sorts of terrain and in all seasons. There are various benefits from this increasing mobility for the urban field and its inhabitants. It allows cottages to be utilized more easily throughout the winter. It broadens the range of outdoor recreational opportunities. It can help reduce the dependence on summer-season business in the economic base of centres in the periphery. The disbenefits of increasing personal physical mobility are also substantial. For example, open space sought out for its lack of congestion can itself become crowded. Many of the new vehicles, such as snowmobiles and trail bikes, require a good deal of space for their use. As open space is used more intensively, the problems associated with the city - petty crime, inadequate municipal services, land-use abuses, and loss of privacy - become the problems of the periphery. Together these conditions could motivate people to seek recreation areas further afield, leaving deteriorating areas behind and bringing new areas under pressure. Catford (1972) concludes that the net effect of increased

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winter use of cottages and snow machines may not favour either the recreation areas themselves or their local governments. Increased tax revenues are likely to be offset by increased expenditures for local services. The expenditures of snowmobilers are neither large nor concentrated in the recreation areas but made in the city or en route to the recreation field. THE EMERGENT URBAN FIELD 'Many people make a mistake in viewing the rural land in the urban field as an empty canvas,1 observes Stephen Rodd (Colloquium on the Toronto Urban Field, 1970). But an 'empty canvas1 it is not. The periphery of the Toronto region contains an active and varied range of urban and urban-stimulated activities. On the one hand, land is being both more intensively and more extensively utilized for permanent settlement. And, on the other, space is being used for a greater variety and a greater volume of transitory activities by urban dwellers. A brief look at each of these processes will help to get some benchmarks for speculation of the future use of the urban periphery. The general pattern of land use in most of the Toronto periphery for three-quarters of a century or more before 1950 was of active farms, small service centres for the agricultural community, abandoned farms, and woodlots. Two other uses were significant in localized areas: stone- and gravelquarrying, particularly along the Niagara Escarpment, and vacation homes along water courses north and east of Toronto. Found and Morley (1972) show the dramatic changes that have occurred in the array of land uses and land owners since 1950 in this region. Table 15.1 illustrates the present set of 'actors' and types of properties. Land uses in the periphery are now dominated by urban-oriented owners who live full- or part-time in the periphery. The 'behavioural environment1 in which these new actors operate will affect the form, the nature, and the pace of development in the periphery. The periphery is also a space resource for the itinerant urbanite. Various forms of recreation — camping, skiing, boating, biking, picnicing, fishing, swimming, snowmobiling — use extensive areas in a transitory manner, i.e., for one or a few days at a time. All these activities have increased in volume substantially in the recent past. Visitors to

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TABLE 15.1 Land-use types and owners of rural land, Toronto urban field, 1972

Rural land uses

1 2 3 4 5 6 7 8 9 10 11 12 13

Prestige rural estate Rural retreat Social and/or ethnic group property Rural non-farm residence Retirement property Property of semi-retired farmer Commercial farm Rural recreation enterprise Public conservation or recreation area Small town residence Small town commercial enterprise Non-agricultural industry Speculative land holding

Owner orientation

Occupancy

urban urban urban rural/urban urban/urban rural rural urban

full-time part-time full/part-time full-time full/part-time full-time full-time part-time

urban rural rural urban urban

part-time full-time full-time non-resident non-resident

SOURCE Adapted from Found and Morley (1972)

conservation areas have been increasing at a rate of about 10 per cent per year for a decade. The same growth rate applies to skiers and to campers in provincial parks. And snowmobile sales have been increasing at around 25 per cent per year for the last half decade. Friedmann and Miller (1965) postulate that three factors have contributed to the growing attractiveness of the periphery for the metropolitan population: (1) greater disposable incomes; (2) more leisure time; and (3) expanded capabilities for mobility. These are, perhaps, obvious explanations, but that does not make them any less important. In addition, it is necessary when dealing with the urban field to grasp the interaction of these factors. Increased incomes allow for the purchase of more mobility and/or leisure-time options, for example. More leisure time along with greater mobility opens up not only larger possible life spaces but also a greater variety of possible living environments for urban dwellers, and so forth. Trends in these factors indicate no diminution in their strength over the next quarter century. A brief examination of these trends will help show the forces which will affect development of the urban field to the year 2000.

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1 Increasing incomes Various forecasts of the level of personal income of Canadians tend to reach the same conclusion: by the end of this century incomes will have risen to about three times their present levels in real terms (Kettle, 1972). This would mean that the average family income could reach $13,00015,000 per year in today's prices. 2 Increasing leisure time The prospects for leisure time for Canadians by the year 2000 are for unstructured time in a person's lifetime to grow from its present 41 per cent to over 48 per cent. Closely associated with leisure time is retirement time, which is expected to undergo an even sharper increase - up by a third to over 12 per cent of a person's lifetime (Kettle, 1971) . In addition to the change in the volume of leisure hours, a more dramatic revolution may be underway in new forms of structuring work time. The flexible work week is already firmly established in some key industries in Canada. For most workers in these industries this means a four-day work schedule; for some it means a three-day week; and for a few it means a monthly commitment of work hours combined with flexible daily starting and quitting times. 3 Increasing mobility The telephone and the automobile have already reduced both time and distance factors for most journeys for urban residents. Residential and commercial activities can remain in contact over extensive areas because of these two devices. One cannot expect substantial changes in them in the next quarter century to produce any significant broadening of life spaces. Rather their effects will be through indirect means. The impact of the automobile will be increased through the increase in its numbers. The two- and threecar family could become the norm. It is expected that the relative cost of a new car, for example, will decline by 1985 to about one-half of what it is today in terms of per capita GNP (Kettle, 1971). As the vehicles are purchased, the variety of life spaces of a family will vastly multiply. The telephone could have a broadened impact through adaptations of existing circuitry to computer-indexed operations for shopping, entertainment, etc. (Dakin, 1972). The mobility offered by the new recreation vehicles must

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also be taken into account. They come on the scene mainly at the termination of the automobile journey from the city. If the latter is assumed to be 100 miles, the new vehicles open up a large array of different terrains (snow, water, swamps, mountains) upwards of 25 to 50 miles away from a cottage. Thousands of acres never before accessible can now be 'enjoyed' by urban dwellers in the periphery. The snowmobile expands the daily life space in winter by 30 to 40 square miles. CONCLUSION The aim of this speculation is to propose a sort of mental matrix combining the three factors of change and the many actors in the urban periphery's future. In general, it would appear that the three factors of increasing income, increasing leisure time, and greater mobility will create an even more urban-oriented periphery around Canadian metropolitan areas than at present. The prestige rural estate, with its full-time urban resident, will become more prevalent, as will the rural retreat or vacation home and the retirement property of present city dwellers. Recreation areas, both public and private, will expand their numbers and, possibly even faster, their scale. Most small towns around Toronto, for example, will be sustained, and many will expand as the number of permanent residents in the periphery increases. Non-agricultural industry could grow, but is not likely to be a significant factor in any case. Commercial farming will be under extreme pressure through the increased demands for rural land for recreational purposes, The extent of the area subject to fairly intensive exploitation by urban residents is likely to increase to 175 miles to the north and northeast of Toronto and to 120 miles on the east. However the most noticeable changes will be a much more intensive use of the space within the roughly 20to 100-mile zone. The total permanent population may not come to exceed the 300,000 proposed for it in the TorontoCentred Region Plan. But it would be misleading to consider that the area be treated as if the size of the resident population were the prime distinguishing feature of its future. It is now part of a spatial field of urban activities, inextricably bound to the future of the metropolitan centre both in terms of prospects and problems.

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What used to be simple relationships of hinterland and centre have become multi-nodes with poly-nuclear patterns. Certain functions are dispersing from the original city to other places in a much larger area ... This is building a process of urbanization we can probably expect more of in the future, evolving entirely new kinds of life styles and settlement patterns. I think it is correct to suppress the notion of separate identity and treat this urban field as a space in which locations can almost occur at random. (Friedmann, Colloquium on the Toronto Urban Field, 1970) NOTES *

1

2

Much of the material used in this section derives from a graduate seminar held in the Department of Urban and Regional Planning, University of Toronto, between 1967 and 1971. The members of that seminar did much to refine and enlarge the notion of the urban field. Material developed in seminar reports by Heather Heaps, Michael Kusner, Peter Hammer, Robert Gravel, John Perry, and Gordon Kumagai is included here and is gratefully acknowledged. These contributions of Metropolitan Toronto migrants to the population growth of small towns in recent years are confirmed by Hill (1973). The result of a simple plotting of a 25-mile contour laterally from each corridor gives an envelope for potential residential development.

REFERENCES Bogue, D.J. 1949. The Structure of the Metropolitan Community: A Study in Dominance and Subdominance. Ann Arbor: University of Michigan Press Catford, M. 1972. Cottage Conversion in Ontario: A Study of Its Extent and Its Potential Impacts. Unpublished graduating essay, Department of Urban and Regional Planning, University of Toronto Colloquium on the Toronto Urban Field. 1970. Edited by G. Hodge. Centre for Urban and Community Studies, University of Toronto Dakin, A.J. 1972. Telecommunications in the Urban and Regional Planning Process. Toronto: University of Toronto Press

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Dawes, W. 1972. The Location of Industries Receiving O.D.C. Forgivable Loans in the Toronto Region, 1967-1971. Unpublished paper, Department of Urban and Regional Planning, University of Toronto Friedmann, J., and Miller, J. 1965. 'The Urban Field,1 Journal of the American Institute of Planners, 31/6: 312-19 Found, W.C., and Morley, C.A. 1972. A Conceptual Approach to Rural Land Use - Transportation Modelling in the Toronto Region. Research Report 8. University of Toronto - York University Joint Program in Transportation Gravel, R. 1968. Urban and Rural Trip Patterns in the Outer Rural Ring of the Metropolitan Toronto Region. Seminar Report 4. University of Toronto, Centre for Urban and Community Studies. Hammer, P. 1968. The Distribution and Impact of Cottages in Toronto's Urban Field. Seminar Report 3. University of Toronto, Centre for Urban and Community Studies Heaps, H. 1968. The Urban Field of Toronto: An Examination of a Sector. Seminar Paper 1. University of Toronto, Centre for Urban and Community Studies Hill, F.I. 1973. "Migration in the Toronto-Centred Region,1 in L.S. Bourne, et al., eds, The Form of Cities in Central Canada: Selected Papers. Toronto: University of Toronto Press Kettle, J. 1971. 'The Leisure-Problem Myth,' Canadian Executive Kettle, J. 1972. 'Footnotes on the Future,1 Canadian Executive Koop, R. 1967. Urban and Rural Migration Flows in Southern Ontario, 1951-1961. Unpublished MSc thesis, University of Guelph Kumagai, G. 1970. Parameters of Personal Physical Mobility in the Toronto Urban Field. Seminar Paper 7. University of Toronto, Centre for Urban and Community Studies Kusner, M. 1968. New Parameters in Rural Land Subdivision. Seminar Paper 2. University of Toronto, Centre for Urban and Community Studies Ontario Department of Tourism and Information, 1971. Analysis of Ontario Cottage Survey. Travel Research Report 55 Ontario Department of Municipal Affairs, Community Planning Branch. 1969. Recreation Tomorrow, Ontario Looks to 1986

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Perry, J. 1970. The Impact of the Snowmobile in Toronto's Urban Field. Seminar Paper 6. University of Toronto, Centre for Urban and Community Studies Rodd, S. 1967. Regional Variations in Net Migration in Southern Ontario, 1951-1961. Unpublished paper Wolfe, R.I. 1965. Parameters of Recreation Travel in Ontario, Department of Highways of Ontario Report No. RB 111

16 The form and function of future communities* BARRY WELLMAN

THE PERSISTENCE OF COMMUNITIES The end of 'community' has been forecast ever since the development of the first cities. Cassandras have warned that the city's increase in scale, density, and heterogeneity over previous forms of settlement would bring an end to in~ formal networks of people with common interests and a sense of group identity, which allows them to take pleasure and profit from each other's company. There were too many people to know, of too many kinds, and crowding would compress these individuals into masses. In North American cities the pastoralist longings of intellectuals and the populace have perpetuated the prevalence of this view of the city as bringing about 'the eclipse of community1 (Stein, 1960; White and White, 1962; Marx, 1964). Formal bureaucratic institutions and impersonal social relationships would be the norm of the city. Systematic empirical research has indicated that communities have pervasively persisted, despite the frequent rumours of their demise. People have continued to develop and maintain informal ties of support and sociability, and bureaucracy has come to supplement and not supplant more informal relationships. Indeed sociological research has indicated that the sheer complexity of bureaucratic structures has fostered the establishment of informal ties which have often developed into communities. Our intensive analysis of an

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area of Metropolitan Toronto has demonstrated the widespread existence and importance of communities in present everyday urban life. We have found little to substantiate the 'myth of the lonely urbanite.' Most people studied have important personal ties, which are frequently organized into systematic networks of relationships, and they are able to use their personal ties for assistance in stressful situations. In the light of this experience, it is difficult to forecast the imminent demise of communities in urban Canada. However social and technological changes may importantly affect the form and function of these communities. In the remainder of this paper we shall discuss some likely changes. Whereas some other papers in this volume are concerned with systems of cities, and some with systems of activities within cities, we are concerned with systems of communities. While communities flourish within an urban and urbane arena, they are, nevertheless, not cities (nor even spatial components of cities) themselves. Therefore this paper will be a general statement, making use of the specific insights into city systems which the other papers in the volume have provided. THE DESPATIALIZATION OF COMMUNITIES The persistence of community ties is predicated on the ability of members of a community to come into contact with one another. For many centuries this meant that communities were often confined to limited spatial areas - neighbourhoods, quarters, turfs, etc. The same area might contain different, perhaps antagonistic, communities, but, because spatially limited life was so intense, with all types of social ties concentrated in the same locale, different groups often attempted to establish exclusive claims to their turfs to reduce the possibilities of insecurity and antagonism. The development of usable rail-based transportation in the past century has facilitated the separation of our work-based communities from other communities. Airline systems have extended the geographical range of this separation even more, so that associates might be linked together in communities by continent-spanning ties. However because of the mass basis of the systems, with limited nodes of entrance and exit, the movement away from quarters was limited to extending only quite specific ties, and extending them only to other dense nodes. The development of railway terminal hotels has

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been supplanted by the development of airport hotels as convenient gathering places. The scheduled, nodal, and highcost nature of railroad and airplane travel has meant that only purposeful and important journeys are likely to be undertaken. This means that many types of community ties are still tightly linked to small localities. The automobile as a means of personal transit has allowed far greater flexibility. Density at terminal nodes is no longer necessary, and the mass accessibility of almost all residents of urban Canada has meant that all sorts of community ties can easily be maintained. Future additions to road networks are being planned, often in conjunction with mass transportation systems. The thrust of planning seems to be in increasing the speed and capacity of existing trunk routes, in developing new high-speed links between secondary points, and in combining the flexibility of automotive-type personal transit with the economies of mass, high-density trunk transit. Such changes will enable urbanites to maintain community ties that are only marginally constrained by spatial limits. Our own research has shown that to a great extent ties with 'intimates' - those outside one's household with whom one feels especially close - are not constrained by locality. Only 13 per cent of the intimates of the Toronto urbanites we studied live in the same neighbourhood as the respondent (most within the same block); only about 25 per cent even live within the same borough (East York). About one-quarter do not live within the boundaries of Metropolitan Toronto, although we suspect that many live within reasonably close proximity (see Wellman, et al., 1973). The expansion of the transportation system means that personal face-to-face ties can easily be maintained with even less spatial constraint. The spatial limits will vary with the type of community tie. For intense and important ties there may be virtually no boundaries on occasions in which community members have to gather personally: the birth or death of a loved one or an important business conference. Other communities, in which ties are not so intense and compelling, will be more sensitive to the ease and cost of spatial mobility. It is likely that there are different classes of community with different spatial limits. How far will stamp-collectors go to get together, as compared with members of a religious sect? In our own research we found that some intimate community

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members maintain their ties primarily by telephone. Either the spatial distances are so great as to discourage most personal contact or the community members are able to provide support, sociability, or service to one another without personal contact. Such ties were no doubt initiated by personal contact, but are now/ for the most part, maintained by telephone. The important thing is that the intimates are known to be there, they form an important part of one other's psychological life space, and they can be mobilized in times of need. With high rates of geographical mobility the maintenance of community by such non-face-to-face means may become increasingly more prevalent as families disperse because of life-cycle changes, and neighbours move away. The development of videophones, adding visual to auditory stimuli, should greatly facilitate the maintenance of community ties without personal contact. The provision of low-cost 'conference1 type calls will facilitate increased non-face-toface interactions among multiple members of the community. A model for such a network is the specialized one of over-the-counter stock trading, in which a great amount of information is conveyed to brokers across the continent by the NASDAQ computer-based telecommunications system. Such a system 'works1 because of the great standardization in the information being exchanged and the minimal need to know other information about fellow members of the network. A person does not need to know much more about the others (not even their names) than that they can deliver (or pay for) the shares bought (or sold). But even here personal communication to get 'inside' or specialized information is necessary for successful membership in the community of stock brokers. It is not necessary that farflung ties be close ties to be useful. Granovetter (1973) has shown that prospects for obtaining jobs are greatly improved if a person has a diverse network of people to whom he or she is only weakly tied - not close friends, relatives, or business associates. The people to whom a person is close tend to know of the same job openings (or lack of them) as he does. If they are colleagues, they may actually be competing with him. On the other hand, people to whom he is only weakly tied are a more mixed lot, with access to a greater variety of information about many different job possibilities. In job hunting there is a latent, real community of members who know each other, but

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just barely enough to help each other out in job acquisition. They are not people with whom a person is in frequent intellectual or social contact, but they are members of an urbanite's community nevertheless. The expansion of the economic range of long-distance communication will expand the geographic range for which such a community will be viable for a given socioeconomic group, and it will similarly open up new ranges of opportunity to maintain such communities for lower-income people. We forecast that there will be increasing use of non-faceto-face media of communication, but that contact will be maintained through a mixture of face-to-face and indirect means. It is unlikely that any new systems will provide all of the information, cognitive and sensory, or the flexibility in altering relationships that face-to-face relationships provide. The possibilities and limits are expressed in Isaac Asimov's speculative novel The Naked Sun, in which all contact is by very sophisticated telecommunication, including love relationships, with the single exception of procreation. Telecommunications should be important in maintaining contact among community members between meetings, especially when the cost of physically coming together is not perceived as worth the content of the message. When group interaction can be easily accomplished by telephonic means, then the maintenance of less intense communities (e.g., recreational stamp collectors) should be facilitated; there should be less need for even intimates to get together in person, despite the ease of spatial access discussed before, and it will become possible to introduce new members to entire communities without personal gatherings. As environmental concerns in Canada appear to be more focused around transportation than communication developments, the enhancement of the community telecommunication systems may be of more strategic importance than the transportation developments discussed earlier. THE INCREASE OF SPECIALIZED COMMUNITIES The more constrained people are in terms of those with whom they can be in contact, the more limitations there will be on the development of specialized communities. If a person is limited in his contacts to those people he can reach in his neighbourhood, then his community ties will be limited

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to those which he can share with his fellow neighbourhood members. Increase in spatial mobility and communications capabilities not only reduces the spatial clustering of communities, but also permits the creation of communities focused around more narrowly specialized interests. If a person has a special interest in an esoteric field, such as modern dance, it is not likely that others who share that passion will live in the same neighbourhood or work in the same place. The only way in which ties between people with similar interests can be maintained - informing each other about the next new dance group that is going to come to some obscure, unpublicized auditorium and then gathering there - is through telephonic means and a high level of flexible personal mobility in the metropolis. Such a group indeed gathers at times. But the specialist in an esoteric field of work, who is baffled by a problem, does not usually get good advice by trotting down the hall to talk with someone out of touch with what he is doing. He gets the advice he needs by using a long-distance telephone call to talk with someone who has similar concerns and whose advice he knows he can trust. The advisor may live half a continent away. In such instances, the more esoteric the field, the more far-flung the community of people who are in it and are interacting with each other. Such interaction will be greatly enhanced with improvements in the high-speed transmission of bulk information. Other authors in this volume have projected the growth in the size of urban areas in central Canada, the increasing importance of urban fields, and the probable development of a St Catharines-to-Oshawa megalopolis. Such an increase in the scale of urban areas, coupled with the projected improvements in transportation and communication media, means that there should be a concommitant increase in the number of people sharing a like interest. While interactive cable systems have often been proposed as a means of easily uniting dispersed people with the same special interest, the undeniable usefulness of such systems in facilitating community development will be limited by the technological fact that members of the 'audience' can only dyadically feed back to the central communications point and not directly interact with each other. The continuance of current government policy in Canada of fragmenting cable systems will severely limit their usefulness in maintaining communities.

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The movement of women into other than housewife roles, accompanied by the institutionalization of day care for children, will create another source of potential recruits into specialized communities, apart from the overall demographic increase. Specialized communities which had heretofore lacked a critical mass to develop into something more than an agglomeration of people with similar interests will thus be in a position to develop. The scale increase is also accompanied by an anonymity not likely to be possible in local communities, so that those whose specialized interests are deviant by community standards will have an easier time in contacting one another, remaining unnoticed, and maintaining a community. The sheer increase in scale may provide something of a countertrend to the despatialization of communities discussed earlier in this paper. There will probably always be some cost to physical mobility; if modern dance groups become popular in many different localities, so that there is no longer only one metropolitan-wide community based on currently small numbers, many such communities should spring up in different localities. The force of this localization trend should be vitiated, however, by the tendency of specialities to become subspecialities. That is, when only one small community of people with a shared interest exists, the sharedness tends to be emphasized at the expense of differences within the group in order to hold the community together. With an increase in numbers, however, more than one group may become viable. Fission may occur on the basis of subspecialization, as ease of contact throughout the metropolis enables the now-divided communities to retain their members. This is a phenomenon frequently observed among doctrinaire political and religious groups. Thus the increase in access, in person and by telephone, coupled with the marked increase in the scale of communities, are all conducive to the development of new specialized urban communities and the enhanced maintenance of currently precarious communities of shared interests. This phenomenon is likely to be accompanied by an increased differentiation of ties between individuals in the metropolis. Whereas before individuals may have shared more than one interest or activity together, the development of specialized communities is likely to weaken holistic communal ties and encourage the fragmentation of communities.

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THE

MULTIPLE COMMUNITIES OF MODERN URBANITES

In the mythical pastoral village, to which cities have always been compared, there was always only one community. That is, not only were all the villagers linked with one another; they were linked to each other by many ties: e.g., kinship, friendship (and enmity), work, and mutual assistance. We have seen that, in Central Canada, communities will be increasingly non-local and specialized in character. This has two important fragmenting consequences, as compared with the holistic pastoral community. It means that each urbanite will probably be involved in a number of communities, with a strong possibility that many or all of the members of each of his communities will not know the members of each of his other communities. It also means that there will be less tendency for communities to encompass all of a group of urbanites' social relationships; in terms of the kinds of interpersonal ties they comprise, communities will tend to be boutiques rather than supermarkets. The involvement of Canadians in a variety of community ties and communities will enable the creative use of contacts made in each of these communities. People will be able to bring the resources gained through membership in one community to bear on problems in another of their communities. To take a typical example: a person's close relatives fearfully let her know at a family get-together that a high-rise development is planned for the relatives' heretofore lowdensity street. Among the people this person sees in her own neighbourhood is a competent, ideologically motivated city planner who is willing to work with her relatives1 neighbourhood group in blocking the development. Only her close community ties with her relatives, and her own and her relatives' ties with their respective neighbours, are able to get the city planner in touch with a group in need of his services. As another example, when abortions were difficult to obtain, women frequently acted in this manner to get information to each other (Lee, 1969). Thus membership in many communities enables one to perform a brokerage role in bringing together people who are in different communities, and who are not themselves linked to each other. Often a person has a certain number of strong interpersonal ties and a certain number of weak ties, organized into a municipality of personal community ties; when information is needed, this person can become an impor-

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tant switching point in getting knowledge or support from one community to another. The importance of strong ties is that a person can ask many things of the people to whom he is tied in such personal communities, even without frequent contacts; the advantage of weak ties is that they tend to be diverse/ and, when help is needed, a person can use many ties in a number of communities for the best leads. Membership in multiple communities is not likely to fragment one's persona to such an extent as to be dehumanizing. An important countervailing tendency is for community ties initially formed on the basis of a single role relationship to become more diffuse over time. Business associates come to be friends, and friends tend to get jobs for one another. The separate ties of married men and women come to be shared. With the development of new interests, the abandonment of old, and the expansion of role relationships, the multiplicity of a person's communities will necessarily often be in a state of stable instability. Involvement in multiple communities can make membership in any single community less important in a person's life. Although communities will also differ in their meaningfulness and importance to an individual, multiple involvement will make it more feasible for an individual to avoid domination by the obligations, norms, and social relationships of a given community. He knows that other options for involvement in other communities will remain open to him if he finds that the demands of a given community become oppressive. Similarly, as a single community loses its claims to all or most of its members' allegiance, it will become more a special interest group and less a wide-ranging force. At present communities of ethnic members who are being discriminated against in Canadian business retain their strength because of the lack of alternatives to which people born into that community can turn. If prejudice and discrimination lessen in urban Canada in the future, then there would be added opportunity for members of such subordinated groups to develop multiple community memberships. THE PERSISTENCE OF NEIGHBOURHOOD COMMUNITIES When people thought of urban areas primarily in spatial terms, then there was a general tendency to equate neighbourhoods with communities. This tendency has persisted to a

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great extent in Canada and is closely related to the pastoralist myth discussed earlier. However, while the greater ease of spatial accessibility and the increasing use of telecommunications to maintain community ties will doubtless lessen the importance of the neighbourhood as a community for many, the neighbourhood will still remain a viable community, albeit one among many, of greater or lesser importance depending on the individual's social circumstances. For some, involvement in neighbourhood communities is quite important. The neighbourhood community plays an important role in the assimilation of newcomers to urban Canada's way of life. As Woodyard pointed out earlier, an in-migrant or an immigrant is likely to move into an area in which his kindred live. There he is more apt to have specialized services close at hand, services which have been attracted to the neighbourhood by the very presence of people like himself. It is especially in enclaves composed of immigrants from cultures very different from the new one that communities will be confined within neighbourhood boundaries, and that the closest approximations to 'urban villages' are likely to occur. Those who are less mobile, for any reason, are more likely to find the neighbourhood one of their important communities. In our own research we have found that those families with children who live in neighbourhoods in which there are also high concentrations of other children are especially prone to neighbour. We suspect that the same is true for the elderly. Childless couples and single people, on the other hand, often use their apartments as headquarters and care little about who lives down the hall. We are coming to see that key determinants of neighbouring are (1) the presence of needs which close-at-hand neighbourly ties may be able to satisfy; (2) the presence of a pool of potential neighbours, given a person's specific needs; and (3) the opportunity for likely neighbours to come into contact with each other (Gates, Stevens and Wellman, 1973). Parents recognize this and choose neighbourhoods in which their children will have access to the 'right' companions. They depend on sorting processes to make these neighbourhood communities relatively homogeneous with respect to socioeconomic status, ethnicity, and, perhaps, life style. At present, children's mobility is limited by their inability to drive automobiles, and often by their inability to make intelligent use of public transit systems when available.

Form and function of future communities

311

The comprehensive development of public transit systems, coupled with basic instruction in map-reading at an early age, might reduce the age of neighbourhood dependence to eight from sixteen. Having already demonstrated a facility with telecommunications devices, this group of children and their families would be able to participate more fully in despatialized, multiple communities. We have found in our research that people who neighbour a good deal often have as well important other communities extending far beyond their local areas. We have found no association between neighbouring and maintaining non-spatial communities. Many people are closely tied to a multiplicity of communities extending throughout the urban area and are also good neighbours. Only a small minority are heavily involved only in neighbourhood affairs. However most retain at least a minimal involvement in order to foster informal social control and to take advantage of what only proximate ties have to offer - the proverbial borrowed cup of sugar and all of its analogues. The foreseeable intensification of the trend away from the neighbourhood as the principal generator of communities makes Blumenfeld's prediction that 'new towns' (and the even more ambitious 'satellite cities') will prove in fact to be 'new boroughs' quite likely. Even the most comprehensively planned community cannot withstand the trend towards despatialization and multiple community membership, although it may afford significant improvements in the quality of one's local life. Similarly Simmons and Lindsay's analysis of long-distance telephoning indicates the decreased viability of smaller regional centres. The multiple communities will be more directly influenced by the two national cultures, and the two dominant metropolises, as concommitants of the processes discussed here. Thus the persistence of communitities is easily foreseeable, but the shifts in their form and function might mean that by 2001 urban communities will be even more amenable to social mapping, rather than spatial mapping, than they are today. CAUTIONARY EPILOGUE The preceding discussion has been essentially catastrophefree in its discussion of future trends. Two foreseeable catastrophic developments may greatly alter the actual manifestation of communities in urban Canada.

312

Urban futures for Central Canada

First, an energy crisis may so greatly increase the cost of personal transportation as to encourage the redevelopment of neighbourhood-based communities. Such a trend would not be all-pervasive however. Mass transit, more efficient in its use of energy, would permit the dispersion of activity, but around densely packed nodes. Telecommunications would presumably also be less affected by such a crisis, and, if costs are kept reasonable, would contribute significantly to the maintenance of despatialized communities of the sort discussed above. Second, the continuation of ethnic prejudice and discrimination in Canada against a significant proportion of the urban population may well lead to the sort of ethnic and racial tension that is endemic in many United States cities. In the event of this occurring in some Canadian cities, the conception and use of the neighbourhood (and block) as a sheltering fortress from 'outsiders' might occur on the part of both dominant and subordinate groups, as has happened in the United States. This would intensify the development of the local area as a community, both as a means of informal social control, and because people might not go elsewhere as frequently. In addition, their movements would be severely limited to those few other areas where they felt safe, comfortable, and "at home.1 NOTE *

I am grateful for the advice and assistance given by fellow members of the Community Ties and Support Systems project: Paul Craven, Stephen Gates, Ann Shorter, Harvey Stevens, Deborah Tannenbaum, and Marilyn Whitaker. Many of the ideas in this paper grew out of discussions with D.B. Coates, Leslie Howard, Nancy Howell, William Michelson, Charles Tilly, Jack Wayne, Harrison White, and fellow participants in the conference on Networks, sponsored by the Mathematical Social Science Board, Camden, Maine, June 1972. Additional support for the research discussed here has been provided under Province of Ontario Health Research Grant No. P.R. 196 and the Laidlaw Foundation, using data originally collected under the auspices of the Clarke Institute of Psychiatry. We are grateful for this support.

Form and function of future communities

313

Asimov, Isaac. 1957. The Naked Sun. New York: Doubleday Gates, Albert S., Stevens, H., and Wellman, B. 1973. 'What makes a good neighbour.' Paper presented to the Annual Meeting of the American Sociological Association, New York Granovetter, Mark. 1973. 'Strength of Weak Ties,1 The American Journal of Sociology. May: 1368-80 Lee, Nancy. 1969. The Search for an Abortionist. Chicago: University of Chicago Press Marx, Leo. 1964. The Machine in the Garden. New York: Oxford University Press Stein, Maurice. 1960. The Eclipse of Community. Princeton, NJ: Princeton University Press Wellman, B. et al. 1973. 'Community Ties and Support Systems,' in L.S. Bourne, et al., eds, The Form of Cities in Central Canada: Selected Papers. Toronto: University of Toronto Press White, M., and White, L. 1962. The Intellectual Versus the City. Cambridge, Mass.: Harvard University Press

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APPENDIX A

Population forecasts for townships in Ontario, 1971-2001

The following listing presents the forecasted populations of Ontario townships from 1971 to the year 2001 in ten-year intervals. The townships are grouped alphabetically by county; the counties are in turn listed in alphabetical order. Population figures for 1951 and 1961 are actual census figures; the list of townships is as it appeared in the 1961 Census. Since incorporated cities, towns, and villages are separate political units and are excluded from the township divisions given in the census, township populations do not aggregate to the total population of a county. Therefore to construct study units which were spatially continuous it was necessary to add the population of a city or town to the surrounding township or townships. Thus the forecasted population of a county, urban region, or census metropolitan area can be obtained by summing the component townships from the following list. The reader should take note that the following forecasts are not intended to be specific target populations for townships. Instead they should be interpreted as demonstrating the outcome of one particular yet comprehensive forecasting technique. The divergent behaviour of some township populations illustrates the important element of this technique the interrelatedness of changes in different areas - and points to the fact that individual forecasts must not be taken out of the context of trends in surrounding townships.

316

Urban futures for Central Canada

Township division

Population in OOs 1951 1961 1971

1981

1991

2001

BRANT COUNTY Brantford Burford Dumfries S Oakland Onondaga

543 47 83 11 11

629 54 90 13 11

722 57 104 13 13

796 75 124 13 14

793 99 173 14 17

865 92 133 16 20

BRUCE COUNTY Albermarle Amabel Arran Brant Bruce Carrick Culross Eastnor Elderslie Greenock Huron Kincardine Kin loss Lindsay St Edmunds Saugeen

10 55 19 59 16 33 25 13 37 18 19 42 31 4 5 43

10 59 18 66 17 33 26 13 36 18 19 44 33 3 5 44

6 66 20 76 20 34 27 13 37 16 20 51 22 3 5 39

4 75 24 94 30 39 30 16 41 17 21 49 5 3 6 40

3 84 27 108 37 52 25 19 45 19 21 45 0 5 5 41

2 92 30 121 46 71 25 24 49 19 23 49 0 6 4 40

CARLETON COUNTY Fitzroy Gloucester Goulbourn Gower N Huntley March Marlborough Nepean Osgoode Torbolton DUFFERIN COUNTY Amaranth Garafraxa E Luther E Melancthon Mono Mulmur

22

23

23

11

19

12

2239

3134

3370

3712

3862

4200

26 19 14 7 8 137 41 7

48 26 16 9 9 197 57 7

94 37 22 58 11 642 77 13

93 46 23 97 19

89 52 27 130 24

103 59 38 156 31

1027

1358

1722

71 23

55 32

61 39

15 10 15 34 51 17

16 11 15 33 67 16

19 12 17 39 107 15

26 12 23 51 152 5

27 8 27 57 188 1

24 1 28 48 229 0

Population forecasts for townships Township division

Population in OOs 1951 1961 1971

317

1981

1991

2001

DUNDAS COUNTY Matilda Mountain Wi lliamsburg Winchester

39 24 45 48

42 25 48 55

42 24 51 56

32 12 69 58

17 0 76 52

12 0 91 72

DURHAM COUNTY Cartwright Cavan Clarke Darlington Hope Manvers

13 26 38 110 93 18

15 31 52 169 109 20

22 37 74 196 118 24

27 41 88 198 103 29

32 46 102 211 111 36

37 55 122 270 126 46

ELGIN COUNTY Aldborough Bay ham Dorchester S Dunwich Malahide Southwold Yarmouth

47 45 17 37 88 37 288

51 51 20 38 104 41 328

53 51 23 31 99 44 357

62 57 23 32 65 40 365

68 70 30 34 40 55 386

79 85 37 36 92 76 476

ESSEX COUNTY Anderson Colchester N Colchester S Gosfield N Gosfield S Maids tone Maiden Mersea Rochester Sandwich E Sandwich S Sandwich W Tilbury N Tilbury W

29 47 44 27 62 45 54 137 38 1442 66 104 31 16

37 57 53 29 78 68 66 168 45 1542 90 286 36 16

46 70 66 34 103 97 83 196 65 1734 99 384 44 17

55 84 81 39 126 112 100 221 89 2259 106 357 51 24

63 98 95 44 145 126 114 246 108 2680 117 364 57 32

74 113 109 48 165 148 130 272 128 3061 128 407 64 40

4 8 5 10 2 8

4 7 5 10 2 7

5 7 4 11 1 7

7 9 3 11 2 6

9 10 1 13 2 5

10 10 0 16 1 5

FRONTENAC COUNTY Barrie Bedford Clarendon Hinchinbrooke Howe Island Kennebec

318

Urban futures for Central Canada

Township division

Population in OOs 1971 1951 1961

1981

436 19 7 11 5 55 23 16 11

639 21 7 11 3 90 30 21 11

792 24 7 12 3 57 36 25 12

921 34 11 15 7 0 23 29 6

GLENGARRY COUNTY Char lottenburgh Kenyon Lancaster Lochiel

53 37 33 57

63 36 36 61

57 34 29 63

GRENVILLE COUNTY Augusta Edwardsburg Gower S Oxford-on-Rideau Wo 1 ford

30 80 21 20 18

49 109 26 23 20

24 56 30 180 20 19 41 22 22 29 17 26 47 8 21 21

9 20 6 8 63

Kingston Lou ghbo rough Olden

Oso Palmers ton Pittsburgh Portland Storrington Wolfe Island

GREY COUNTY Artemisia Bentinck Collingwood Derby Egremont Euphrasia Glenelg Holland Keppel Normanby Osprey Proton St Vincent Sarawak Sullivan Sydenham HALDIMAND COUNTY Canborough Cayuga N Cayuga S Dunn Moulton

1991

2001

1057

1354

42 14 17 13 0 9 31 0

46 17 18 17 0 4 34 0

20 38 9 67

0 45 0 75

0 46 0 81

55 109 31 25 20

56 114 26 27 30

48 102 17 28 39

56 129 12 25 44

23 66 31 193 19 17 44 22 22 28 16 25 54 11 20 22

22 73 33 205 19 14 24 23 24 31 17 27 57 16 21 24

20 81 33 204 30 12 9 30 28 39 19 36 54 24 31 32

28 85 44 216 43 15 12 41 35 51 23 41 51 29 39 37

35 98 55 220 49 20 23 52 38 65 31 43 45 36 38 42

11 24 5 10 73

13 26 7 12 83

14 22 10 14 87

14 21 15 15 94

17 26 18 19 102

Population forecasts for townships Township division

Population in OOs 1951 1961 1971

319

1981

1991

2001

Oneida Rainham Seneca Sherbrooke Walpole

30 15 34 3 43

36 17 42 3 48

39 20 56 4 54

40 23 55 6 62

51 26 32 7 61

65 34 29 9 71

HALIBURTON COUNTY An son Bicroft Cardiff Dysart Glamorgan Lutterworth Monmouth Sherborne Snowdon Stanhope

16 0 4 29 4 3 5 3 4 5

18 8 5 28 4 3 6 4 4 5

20 5 4 30 4 4 6 3 4 6

25 18 5 29 5 5 5 10 5 1

25 15 5 25 5 8 8 19 6 0

17 37 6 12 6 10 10 24 7 0

HALTON COUNTY Esquesing Nassagaweya Trafalgar

103 148 187

205 490 373

HASTINGS COUNTY Bangor Car low Dungannon Elzevir Faraday Herschel Hunger ford Huntingdon Limerick Madoc Marmora Mayo Monteagle Rawdon Sidney Thurlow Tudor Tyendinaga Wollaston

10 5 6 6 23 0 40 15 2 29 25 3 15 33 206 265 5 38 7 17 11

HURON COUNTY Ashfield Colborne

303

420

567

725

1509

2177

2508

3085

466

424

451

599

9 4 11 6 41 6 42 15 3 30 25 4 12 34 262 355 5 43 7

8 3 8 6 35 5 40 16 2 28 29 3 10 36 283 401 4 43 5

10 2 16 7 56 14 34 10 1 29 42 10 1 46 304 406 6 60 3

12 2 14 8 54 10 36 6 0 28 50 27 0 58 391 404 7 70 2

14 4 35 9 127 34 43 0 0 28 54 50 0 68 450 456 8 84 2

16 12

17 13

35 15

46 16

57 19

320

Urban futures for Central Canada

Township division

Population in OOs 1951 1961 1971

1981

1991

2001

Howick Hullett McKillop Morris Stanley Stephen Tucker smith Turnberry Usborne Wawanosh E Wawanosh W

65 27 35 28 44 17 23 19 45 53 40 42 11 11

82 27 36 27 54 16 23 28 45 54 43 45 11 11

88 27 37 29 49 15 24 14 37 50 43 49 10 12

79 16 33 34 35 11 39 1 36 52 57 62 11 16

74 28 31 40 26 23 50 0 57 74 73 81 12 22

72 10 33 49 20 13 60 0 76 96 82 103 12 26

KENT COUNTY Camden Chatham Dover Harwich Howard Or ford Raleigh Romney Tilbury E Zone

52 372 54 93 51 21 57 25 43 15

57 463 45 102 53 21 52 29 44 19

58 523 44 161 55 20 65 34 48 11

70 560 61 175 57 7 76 40 49 4

86 608 85 202 74 6 99 46 47 0

98 675 94 232 78 3 111 53 46 0

LAMBTON COUNTY Bosanquet Brooke Dawn Enniskillen Euphemia Moore Plympton Sarnia Sombra Warwick

33 27 20 60 13 49 46 416 31 33

54 27 18 70 12 62 54 626 35 36

50 27 18 76 12 74 62 707 40 38

21 33 32 114 21 79 72 690 62 56

0 38 45 153 28 87 86 769 80 78

0 43 56 191 35 99 111

16 57 4 10 4 64 8

18 59 4 8 3 67 10

20 67 5 7 2 71 15

28 76 9 15 7 80 21

41 94 11 21 6 118 29

Goderich Grey

Hay

LANARK COUNTY Bathurst Beckwith Burgess N Dalhousie Darling Drummond Elmsley N

1000

88 97 61 124 13 26 6 165 40

Population forecasts for townships

Township division

Population in OOs 1951 1961 1971

1981

1991

321

2001

Lanark Lavant Montague Pakenham Ramsay Sherbrooke S

18 2 106 12 42 6

17 2 142 11 49 5

16 1 140 11 56 4

13 0 88 12 51 1

13 0 45 13 25 0

9 0 8 13 10 0

LEEDS COUNTY Bastard Crosby N Crosby S Elizabeth town Elmsley S Escott Front Kitley Leeds Front Leeds Rear Yonge Front Yonge Rear

23 17 14 180 8 9 16 71 18 12 16

24 16 13 243 10 9 16 81 19 14 19

22 15 13 262 14 10 17 85 21 15 20

0 22 8 280 22 12 18 99 25 22 23

0 26 3 272 28 12 23 105 30 23 26

0 27 3 318 33 13 15 108 30 29 28

4 4 34 8 36 14 7 14 58 12

5 4 37 7 63 17 8 14 67 11

5 3 40 6 96 22 9 12 73 11

5 1 30 9 128 26 6 16 51 13

3 0 23 10 142 27 2 20 28 11

3 0 28 8 167 33 2 22 28 12

13 40 23 74 17 44 451

16 58 25 134 23 50 958

14 43 23 251 23 47

10 35 1 270 12 43

16 30 0 265 10 33

23 22 0 309 13 19

1190

1202

1311

1980

15 24 71 13

17 28 94 19

20 32 119 22

16 40 128 35

13 51 145 54

14 62 168 72

LENNOX AND ADDINGTON Ado Iphus town Amherst Island Camden E Denbigh Ernestown Fredericksburgh N Fredericksburgh S Kaladar Richmond Sheffield LINCOLN COUNTY Caistor Clinton Gainsborough Grimsby N Grimsby S Louth Niagara MIDDLESEX COUNTY Adelaide Biddulph Car ado c Delaware

322

Urban futures for Central Canada

Township division

Dorchester N Ekfrid Lobo London McGillivray Metcalfe Mosa Nissouri W Westminster Williams E Williams W MUSKOKA COUNTY Brunei Cardwell Chaffey Draper Franklin Freeman McLean Macaulay Medora Monck Morrison Muskoka Oakley Ridout Ryde Stephenson Stisted Watt NIPISSING COUNTY Bonfield Caldwell Calvin Cameron Chisholm Ferris E Ferris W Field Mattawan Papineau Springer Widdifield

Population in OOs 1951 1961 1971

1981

1991

2001

35 28 21

53 30 26

63 33 38

55 39 52

68 44 61

91 51 72

1138

1754

2274

2446

2648

2899

23 8 20 26 151 9 19

23 8 19 30 58 10 21

23 8 20 37 66 10 21

20 8 28 46 245 6 28

18 9 35 59 308 2 37

24 11 41 72 289 1 49

9 3 17 5 6 8 4 34 20 10 46 6 2 1 2 10 36 8

10 2 23 5 7 9 8 33 24 12 49 8 1 2 2 10 34 7

11 1 29 4 7 10 10 69 15 12 71 9 1 2 1 8 95 7

21 3 20 4 6 6 1 147 14 11 138 4 1 2 1 1 196 11

28 6 13 1 5 0 0 228 9 10 202 0 4 3 2 0 333 15

33 5 6 0 3 0 0 298 7 9 234 0 3 5 3 0 469 20

13 15 5 2 8 10 25 11 6 38 69 214

17 18 5 1 9 18 50 10 1 40 86 358

16 18 5 1 8 24 80 8 0 35 94 410

15 20 3 5 5 23 84 0 19 52 15 472

19 20 2 12 3 14 63 0 62 84 0 500

30 18 1 13 0 19 86 0 56 85 0 680

Population forecasts for townships

Township division

323

Population in OOs 1951 1961 1971

1981

1991

2001

NORFOLK COUNTY Charlotteville Houghton Middleton Town send Walsingham N Walsingham S Windham Woodhouse

46 20 31 66 25 28 73 133

53 22 39 76 29 32 93 158

57 21 41 82 29 31 96 176

78 43 47 88 47 38 120 189

114 69 67 112 74 54 169 227

145 86 89 137 96 67 209 270

NORTHUMBERLAND COUNTY Alnwick Brighton Cramahe Haldimand Hamilton Monaghan S Murray Percy Seymour

6 40 31 24 106 6 30 29 57

6 48 34 28 157 7 45 29 60

7 58 37 30 182 8 57 30 64

10 65 37 33 204 10 76 38 66

14 67 34 30 232 12 88 47 67

21 87 41 35 261 13 112 55 75

ONTARIO COUNTY Brock Mara Pickering Rama Reach Scott Scugog Thorah Uxbridge Whitby Whitby E

36 21 103 7 44 17 3 19 38 102 431

40 24 185 9 53 19 4 23 51 209 650

45 30 342 10 67 25 6 30 69 252 1255

55 16 438 13 93 33 6 32 80 290 1769

63 1 525 9 136 39 7 45 92 323 2067

70 0 629 2 191 46 8 37 112 442 2468

OXFORD COUNTY Blandford Blenheim Dereham Nissouri E Norwich N Norwich S Oxford E Oxford N Oxford W Zorra E Zorra W

12 39 89 24 35 27 178 78 26 51 24

15 44 109 28 40 30 229 86 34 58 27

14 46 119 33 43 31 278 95 28 59 28

11 46 153 31 69 39 335 106 17 71 31

6 54 175 30 89 56 357 113 25 83 28

8 68 216 33 99 71 430 126 33 90 27

324

Urban futures for Central Canada

Township division

PARRY SOUND COUNTY Armour Carling Chapman Christie Foley Hagerman Himsworth N Himsworth S Humphrey Joly McDougall McKellar McMurrich Machar Nipissing Perry Ryerson Strong

Population in OOs 1951 1961 1971

17 2 6 5 5 3 12 8 5 1 70 4 5 12 5 13 4 13

17 3 5 5 8 3 18 10 6 1 82 4 4 14 6 13 4 14

1981

1991

2001

8 7 0 16 2 3 17 63 2 12 73 3 0 12 17 14 0 18

5 9 0 23 4 3 12 93 0 25 73 2 0 7 29 16 0 17

1 10 0 28 0 4 14 113 0 37 71 2 0 6 38 18 0 15

63 66

52 78

62 98

1719

1044 2332

13

1304 3773

0

1470 4038

14

9

17 4 5 5 3 3 21 29 5 0 80 4 4 14 9 13 3 16

PEEL COUNTY Albion Caledon Chinguacousy Toronto Toronto Gore

29 32 136 333 25

51 43 260 748 11

PERTH COUNTY Blanshard Downie Easthope N Easthope S Ellice Elma Fullarton Hibbert Logan Mornington Wallace

58 211 17 19 22 32 35 15 22 34 54

64 230 21 23 27 33 38 16 22 36 61

65 263 21 28 28 36 41 15 22 38 68

92 334 19 16 27 38 50 11 19 45 50

127 385 15 7 24 39 60 7 14 50 52

123 319 14 4 25 46 68 6 15 55 77

22 27 7 5 38

25 29 9 4 53

27 31 10 4 54

36 27 9 0 68

46 20 4 7 78

57 23 9 2 127

PETERBOROUGH COUNTY Asphodel Belmont Burleigh Chandos Douro

76 57 722

Population forecasts for townships Township division

Population in OOs 1951 1961 1971

325

1981

1991

2001

Duiraner Ennismore Galway Harvey Monaghan N Otonabee Smith

14 5 3 9 396 33 41

14 6 2 8 510 46 47

16 15 2 10 585 42 65

2 34 9 19 702 19 99

0 50 16 28 816 16 148

0 56 14 27 838 19 192

PRESCOTT COUNTY Alfred Caledonia Hawkesbury E Hawkesbury W Longueuil Plantagenet N Plantagenet S

30 15 32 102 19 30 25

31 14 31 121 21 28 23

29 12 28 131 22 20 17

26 15 31 115 26 17 5

26 18 30 89 27 9 0

23 28 34 117 28 10 6

30 9 96 13 9 8 17

39 10 110 14 10 8 16

43 12 98 15 10 9 17

46 14 49 0 9 1 1

60 12 6 0 4 0 0

67 12 0 0 1 0 0

12 5 5 12 10 16 4 10 25 4 23 6 87 76 132 62 6 7 46 24

13 5 3 20 10 14 2 9 28 2 25 5 105 92 177 138 7 7 97 26

13 5 3 24 10 12 2 8 26 3 22 4 107 101 172 135 7 7 88 25

14 2 11 6 18 16 2 0 22 5 7 9 96 148 129 95 5 3 47 27

17 0 6 0 26 22 0 0 0 2 0 16 91 278 100 118 2 4 60 30

22 0 0 0 30 24 2 0 0 8 0 16 84 413 57 46 0 6 0 38

PRINCE EDWARD COUNTY Ameliasburg Athol Hallowell Hillier Marysburgh N Marysburgh S Sophiasburg RENFREW COUNTY Admaston Algona N Algona S Alice Bagot Bromley Brougham Brudenell Grattan Griffith Hagarty Head Horton McNab Pembroke Petawawa Radcliffe Raglan Rolph Ross

326

Urban futures for Central Canada

Township division

Population in OOs 1971 1951 1961

1981

1991

2001

Sebastapol Sherwood Stafford Westmeath Wilberforce

4 23 15 25 26

4 27 31 25 29

8 29 37 18 13

12 22 9 7 0

16 12 18 0 0

21 11 59 0 0

RUSSELL COUNTY Cambridge Clarence Cumberland Russell

34 68 40 32

37 77 54 38

39 82 92 41

54 58 123 35

40 36 149 27

60 53 180 26

Tecumseth Tiny Tosorontio Vespra

13 101 28 37 42 3 27 130 188 29 24 167 57 39 14 155

16 137 34 48 69 3 30 151 253 42 32 197 76 44 18 246

22 136 59 71 105 4 36 180 290 51 23 228 99 54 20 311

12 175 94 87 101 11 56 204 264 76 6 245 105 67 22 321

5 256 123 107 96 19 74 245 253 61 0 268 100 74 19 319

4 277 148 120 118 29 85 281 258 121 0 325 98 77 16 340

STORMONT COUNTY Cornwall Finch Osnabruck Roxborough

383 28 34 33

479 27 34 31

509 26 33 29

583 24 41 30

584 16 40 35

555 29 48 34

6 3 2 19 23 30 5 27 116 11 25

6 3 2 19 25 34 5 28 133 12 26

6 3 2 20 31 44 6 31 150 13 30

12 5 2 23 34 69 6 36 161 17 44

18 9 1 24 39 94 8 40 169 20 56

19 11 2 25 44 105 9 47 165 30 64

SIMCOE COUNTY Ad Jala Essa Flos Gwillimbury W Innisf ill Matchedash Medonte Nottawasaga Orillia

Oro Sunnidale

Tay

VICTORIA COUNTY Bexley Garden Dalton Eldon Emily Fenelon Laxton Mariposa

Ops Somerville Verulam

Population forecasts for townships

Township division

WATERLOO COUNTY Dumfries N Waterloo Wellesley Wilmot Woolwich WELLAND COUNTY Bertie Crowland numbers tone Pelham Stamford Thorold Wainfleet Willoughby WELLINGTON COUNTY Arthur Eramosa Erin Garafraxa W Guelph Luther W Maryborough Minto Nichol Peel Pilkington Puslinch WENTWORTH COUNTY Ancaster Beverly Binbrook Flamborough E Flamborough W Glanford Saltfleet YORK COUNTY Etobicoke Georgina Gwillimbury E Gwillimbury N King Markham

Population in OOs 1951 1961 1971

243 831

1981

1991

327

2001

322

434

434

571

568

46 66

1226 51 78

1809 52 99

2109 56 120

2410 57 134

2899 60 151

73

88

110

121

124

135

142 274 121 44 406 143 35 29

195 379 214 71 533 177 47 51

367 463 262 129 652 229 55 68

646 447 307 168 723 226 60 56

801 553 469 195 791 240 78 64

890 864 729 236 917 298 97 118

60 24 32 48

67 30 42 54

61 35 58 71

59 38 72 107

62 36 77 134

58 39 90 158

321 12 25 56

454 12 26 58

609 10 29 62

726 11 19 88

817 8 20 122

937 5 35 151

29 27

34 29

43 33

55 17

63 10

72 6

11 29

12 35

15 35

12 27

15 26

20 30

2159 41 13 112 110 24

2873 50 25 168 199 47

3228 61 38 945 258 61

3386 69 52 2134 314 71

3661 86 53 3320 352 72

3797 108 81 4401 407 84

113

224

273

310

363

420

850

1986 38 192 56 128 341

2822 28 282 120 128 366

3096 10 380 155 108 350

3502 2 426 174 106 364

4644 3 529 213 157 562

30 97 27 74 143

328

Urban futures for Central Canada

Township division

Population in OOs 1951 1961 1971

1981

1991

2001

Scarborough Vaughan Whitchurch York York E York N

562 114 102 8007 808 945

2172 190 193 8321 909 2796

4087 320 256 8504 1309 5891

4782 366 282 8522 1432 6889

6655 433 370 8529 1363 9149

3321 291 248 8456 1049 4811

APPENDIX B

Population forecasts for cities in Central Canada, 1971-2001 Compiled by LARRY S. BOURNE, P.O. HARPER, JAY SIEGEL, and D. THACKRAY

1

INTRODUCTION

The place to begin a study of forecasting is with an inventory of existing studies. This appendix provides population forecasts for urban areas in Central Canada (Ontario and Quebec) taken from a sample of national and regional surveys, as well as a selection of statistics provided by local authorities. Statistics are presented for 21 cities in Ontario and 11 in Quebec. A forecast is included only if it projects to 1990 or beyond. For each city reference is given for the year, source, and method of projection. A list of abbreviations and extensive notes on the methods and sources used precede the forecasts. The urban definitions employed here are based on the 1966 Census of Canada. Several modifications were made in these definitions for the 1971 Census.1 For example, several new Census Metropolitan areas were created: Chicoutimi-Jonquiere in Quebec, Thunder Bay and Niagara-St Catharines in Ontario. Some centres and major urban areas statistically disappeared ********** 1

For detailed descriptions of these modifications see F. Ricour-Singh, Census Metropolitan Areas: Revision of the Concept, Criteria and Delineations for the 1971 Census, Geography Section, Census Division, Statistics Canada, Ottawa, 1972.

330

Urban futures for Central Canada

with the expansion of metropolitan boundaries in 1971. For instance, Brampton was incorporated into the Toronto census metropolitan area; St Thomas was added to the London metropolitan area; the major urban area of Niagara Falls was merged with St Catharines; and Arvida, Chicoutimi-Nord, and Kenogami were grouped with Chicoutimi-Jonquiere. The decision not to delete individual tables for the larger of these cities has been made to ensure continuity of historical data and in recognition of the fact that most existing population projections predate the 1971 Census. Nevertheless the projections of the Centre for Urban and Community Studies were rerun on the basis of preliminary population figures for 1971 and are included here under CUCS (1972). 2

LIST OF CITIES

ONTARIO Census metropolitan areas 1 Hamilton 2 Kitchener-Waterloo 3 London 4 Ottawa-Hull 5 Sudbury 6 Toronto 7 Windsor Census urban areas 8 Brampton 9 Brantford 10 Cornwall 11 Guelph 12 Kingston 13 Niagara Falls 14 Oshawa-Whitby 15 Peterborough 16 Sarnia 17 Sault Ste Marie 3

18 19 20 21

St Catharines Thunder Bay Timmins Welland

QUEBEC Census metropolitan areas 1 Montreal 2 Quebec Census urban areas 3 Chicoutimi—Jonquiere 4 Drummondville 5 Granby 6 St Jean 7 St Jerdme 8 Shawinigan 9 Sherbrooke 10 Trois Rivieres 11 Valleyfield

LIST OF ABBREVIATIONS

BOD BSQ CHSS

Births-over-death ratio Bureau de la Statistique du Quebec Canadian Highway Systems Study

Population forecasts for cities

331

CMA CMHC CUCS

Census Metropolitan Area Central Mortgage and Housing Corporation Centre for Urban and Community Studies, University of Toronto DBS Dominion Bureau of Statistics (now Statistics Canada) DMA Department of Municipal Affairs (Ontario) IQASEP Institute for the Quantitative Analysis of Social and Economic Policy, University of Toronto MTPB Metropolitan Toronto Planning Board n/a Not available n.d. No date NM Net migration ODTE Ontario Department of Treasury and Economics OWRC Ontario Water Resources Commission p.a. per annum p.d. per decade SRG Systems Research Group (Toronto) * Figure given is the actual 1966 Census figure + Figure given is the actual 1971 Census figure for the revised urban area (if appropriate) and therefore may not be comparable to earlier figures 4

NOTES ON EXTENSIVE METHODS AND SOURCES (by method code)

ft. Cohort survival with age-specific projections for fertility, mortality, and net migration. Fertility Assumption used was that all age-specific rates will decline by 3-5 per cent per annum until 1971 and then remain constant. Mortality Age-specific mortality rates are expected to decline as follows: Age group

Percentage

0-1, 1-2, 2-3 3-4, 35-9, 40-4 25-9, 30-4, 45-9, 50-4, 55-9, 60-4, 80-4, 85+ 5-9, 10-14, 15-19 , 20-4, 65-9 , 70-4, 75-9

25-34 15-24 5-14 0-4

**********

2

Ontario Department of Treasury and Economics, Preliminary Population Predictions for Ontario 1971-1991, Economic Analysis Branch, December 1968; Ontario Department of Treasury and Economics, Ontario Population Projections 1966-2001, Municipal Projections, September 1970.

332

Urban futures for Central Canada

Net migration B

50,000 persons per year.

Cohort survival with the following age-specific assumptions regarding fertility, mortality, and net migration for the major urban areas:3 Fertility The rates used were based on Illing's median rates^ scaled to the urban areas. Mortality The mortality rate is expected to decline in an exponential manner chosen to replicate closely Illing's mortality improvement rates from 1965-1980. Net migration Expected to remain constant at the average annual rate for the 1961-66 period for each area.

C

Population forecasts prepared by the Centre for Urban and Community Studies, University of Toronto, are based on a logistic extrapolation of past trends. The individual urban area populations for previous census periods^ as a percentage of (1) Canada and (2) the province (either Ontario or Quebec) are projected using the locristic function: "«- */