Patterns of Residential Movement in Metropolitan Toronto 9781487575410

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PATTERNS OF RESIDENTIAL MOVEMENT IN METROPOLITAN TORONTO

University of Toronto DEPARTMENT OF GEOGRAPHY RESEARCH PUBLICATIONS

l. THE HYDROLOGIC CYCLE AND THE WISDOM OF GOD: A THEME IN GEOTELEOLOGY by Yi-Fu Tuan 2. RESIDENTIAL WATER DEMAND AND ECONOMIC DEVELOPMENT by T.R. Lee 3. THE LOCATION OF SERVICE TOWNS : AN APPROACH TO THE ANALYSIS OF CENTRAL PLACE SYSTEMS by John U. Marshall 4. KANT'S CONCEPT OF GEOGRAPHY AND ITS RELATION TO RECENT GEOGRAPHICAL THOUGHT by J .A. May 5. THE SOVIET WOOD-PROCESSING INDUSTRY : A LINEAR PROGRAMMING ANALYSIS OF THE ROLE OF TRANSPORTATION COSTS IN LOCATION AND FLOW PATTERNS by Brenton M. Barr 6. THE HAZARDOUSNESS OF A PLACE: A REGIONAL ECOLOGY OF DAMAGING EVENTS by Kenneth Hewitt and Ian Burton 7. RESIDENTIAL WATER DEMAND : ALTERNATIVE CHOICES FOR MANAGEMENT by Angelo P. Grima 8. THE ATMOSPHERIC ENVIRONMENT: A STUDY OF THERMAL COMFORT AND PERFORMANCE by Andris Auliciems 9. URBAN SYSTEMS DEVELOPMENT IN CENTRAL CANADA : SELECTED PAPERS edited by L.S. Bourne and R.D. MacKinnon IO. SPATIAL EVOLUTION OF MANUFACTURING : SOUTHERN ONTARIO 1851-1891 by James M. Gilmour 11. THE FORM OF CITIES IN CENTRAL CANADA : SELECTED PAPERS edited by L.S. Bourne, R.D. MacKinnon, and J .W. Simmons 12. IRISH SETTLEMENTS IN EASTERN CANADA : A STUDY OF CULTURAL TRANSFER AND ADAPTATION by John J . Mannion 13. PATTERNS OF RESIDENTIAL MOVEMENT IN METROPOLITAN TORONTO by J .W. Simmons

Patterns of residential movement in Metropolitan Toronto

James W Simmons with the assistance of Alan Baker and Marie Truelove

PUBLISHED FOR THE UNIVERSITY OF TORONTO DEPARTMENT OF GEOGRAPHY BY THE UNIVERSITY OF TORONTO PRESS

© University of Toronto Department of Georgraphy 1974

Published by University of Toronto Press Toronto and Buffalo Printed in Canada Reprinted in 2018 ISBN

0-8020-3328-8

ISBN 978-1-4875-7260-0 (paper)

Acknowledgments

This study was initially conceived by Alan Baker during the winter of 1965, and has been proceeding intermittently ever since . For a variety of technical reasons, the major portion of the analysis was delayed until the last two years, and this report is sadly overdue . From the very start, however, it has helped stimulate other research and discussion on the complex problem of household relocations within cities. Papers on various aspects of residential relocation have been disseminated and several graduate students have made their own contributions. At the same time the existence of the study has linked this research group to others sharing the same interest. The stimulation provided by colleagues such as Larry Brown , Eric Moore, Bill Clark, and Bryn Greer-Wootten is gratefully acknowledged. The initial research was sponsored (with a great deal of patience) by the Canadian Council on Urban and Regional Research. Later on the Ontario Institute for Studies in Education and Bell Canada, through the University of Toronto's Centre for Urban and Community Studies, also provided assistance . Larry Bourne, now the director of the Centre has been a continual source of encouragement and suggestion . During the five years of work on this particular study, a great number of people have made contributions . Many of them were involved in now-forgotten blind alleys , and will not recognize the final results, but their assistance is appreciated nonetheless. Sandy Fraser, Lyndhurst Collins, Brian Smith, and Pat Everts all helped out in the initial programming period, a time when the ground rules of the study changed from day to day. During the later stages, Siegfried Schulte became an invaluable resource person for the programming problems. V

The Ontario Department of Highways' representatives, who provided the data set and its back-up material, were Gerry Johnston, Paul De Valence, and John O'Flynn. Invariably, they were helpful and generous with their time. The cooperation of the Metro Toronto Planning Board and its Director, Woytiech Wronski, is also appreciated. The bulk of the labour in preparing the manuscript for publication was done by Barbara Muthig and Pat Mims, the typists, while the cartography was done by Jane Ejima under the supervision of Geoff Matthews. The permission to reproduce Figure 2.4 from Larry Brown, Eric Moore, Larry Bourne, and the Oxford Press is acknowledged. As a final personal note, I wish to thank my colleagues Fred Hill, and Marie Truelove for their substantial assistance . Not only did they generate massive information inputs, but their questions and comments have greatly stimulated and modified this work. Alan Baker initiated this study . It was his idea and he provided the initial impetus, generated the funds and got people working. Although other demands on his time reduced his active participation later on, he was always available for quick consultation on themes, programs, and interpretations. JAMES W. SIMMONS

University of Toronto

vi

Contents

ACKNOWLEDGMENTS/v

Migration in an urban setting / 3 II

The conceptual background / 17 III

The data source: MTARTS / 32 IV

Over-all movement patterns/ 47 V

Movements of household subsets / 64 VI

Predictors of movement patterns/ 84 VII

Stochastic models / I 02

VIII

Implications / 115 Bibliography / 127 Appendix / 135

Tables

1.1 Housing demand: Metro Toronto, 1951-71 1.2 Housing supply: Metro Toronto, 1951-66

2.l In-migrants to Metro Toronto, 1956-61 2.2 Migration rates by age and sex 3.l 3.2 3.3 3.4 3.5

Evaluating the sample: household size Evaluating the sample: areal units Households and housing stock Household movements between Metro and the Zone totals

MT ARTS

Region

4.l Flow matrix parameters 4.2 Eigenvalues from correlation matrices 4.3 Migration subsystems 5.l 5.2 5.3 5.4 5.5 5 .6 5.7 5.8

Similarities among flow matrices Flow matrix parameters - size of household Flow matrix parameters - age of household Flow matrix parameters - life cycle stage Flow matrix parameters - household income Flow matrix parameters - occupation of household head Flow matrix parameters - workplace of household head Flow matrix parameters - time of move

6.1 6 .2 6.3 6.4 6.5 6.6

Correlation matrix - in and out migration Factor analysis of social characteristics Factor score differences Correlations with the flow matrix Correlations and regressions (18 zones) Characteristics of households

7 .1 7 .2 7.3 7.4

The transition matrix of FC 1 Stationarity tests, household movement Stationarity of origin states Markov parameters by income and life cycle groups

8.1 In-migrant composition, 1956-61 8.2 New housing and mobility

Figures

1.1 The study area

l.2 1.3 l.4 1.5 1.6

Toronto: growth and change, 1851-1971 Recent components of growth Age structure of the Metro population, 1941-66 Average price of Metro housing Patterns of social change, 19 5 1-61

2.1 2.2 2.3 2.4 2.5 2.6 2.7

Migration rates over time Migration rates by age Rates of in-movement to the Toronto Census Metropolitan Area , 1956-61 A model of the residential relocation process Distributions of housing opportunities The bias of migration fields Migration lifelines

3.1 3 .2 3.3 3.4 3.5 3.6

MTARTS study area Refining the sample Household movements - Metro, I 958-64 Origins, destinations and net movements Out-movement rates Per cent moves within zone

4.1 The flow matrix - 62 zones 4.2 Total flows

4.3 4.4 4.5 4.6 4.7 4.8 4.9 4.10

Net flows Scaling techniques Ratio scale Deviation scale Residential moves by distance Resultant movement by zone Migration subsystems Composite migration subsystems

5.1 5.2 5.3 5.4 5.5 5.6

Flow Matrix - 18 zones Variation in flows by household size Variation in flows by household income Variation in flows by occupation of household head Variation in flows by workplace of household head Variation in flows by time of move

6.1 6.2 6.3 6.4 6.5

Mover models: residuals Social trips Residuals from the gravity model 'Familism' moves ' Social Class' moves

7.1 The limiting vector 8.1 Changes in the number of dwelling units, 1956-66 8.2 Patterns of net migration

PATTERNS OF RESIDENTIAL MOVEMENT IN METRO POLIT AN TORONTO

I

Migration in an urban setting

Each year one household in five changes residence. A new home is sought out, the family possessions are packed up and moved, and the process of adjustment to a new neighbourhood begins. By virtue of the move the environment is altered as well. One neighbourhood gains and one neighbourhood loses a family of certain characteristics - four persons, three males, of British descent, with one television set and two cars. The complex relationship between the individual household and the aggregate social structure is the reason for much of the recent attention to intra-urban migration. RATIONALE

An examination of the process of household relocation reveals a great deal about a city. The gross pattern of movement indicates the degree of spatial integration among various parts of the metropolitan area. Net flows reveal the magnitude and character of social change. The various aspects of the movement decision who, when, why, where - reflect the relationship between individuals or households and their immediate environment: how they use it, how they perceive it, what their priorities are. Although assumptions about household relocation are implicit or explicit in every model of urban development, it has been difficult to verify these statements or to explore the relocation process. Intra-urban migration is a complex process undertaken by a wide variety of households, living in a wide variety of environments, and moving for a wide variety of reasons. The simplest infonnation on change of residence is expensive to obtain and code, and institutions 3

such as the census or municipal planning agencies have not yet felt it necessary to build up such data sets. Within the past decade, however , information on intra-urban migration has been greatly expanded. The census agencies in Canada and the United States have begun to monitor rates of movement by location and by subgroup, effectively answering the question 'who moves?' The question 'why do they move?' has been investigated even more recently in a series of nation-wide surveys (Lansing and Mueller 1964; Butler et al. 1969) in the U.S., which have identified the major reasons for moving, the factors considered in choosing a new home, and the diversity of preferences in the urban environment. The next problem 'where do they move?' is tackled in this study. Using data gathered from a metropolitan-wide sample of households in Toronto the basic spatial patterns of movement and the variations in those patterns for different subsets of the population are described. Perhaps the major contribution is the examination of the full range of household types rather than just the young family choosing a home or the occupants of a single area which is about to be razed. Throughout the text the information gathered in Toronto is compared to findings obtained elsewhere, and the implications of mobility patterns for models of urban development are discussed . Although the main thrust of this study is descriptive, three other concerns are investigated in part. There is a continuing interest in the problems of analysis and presentation of flow data - how to reduce the complexity of a flow matrix in some meaningful manner. The temporal evolution of the housing market and the residential pattern is also of interest, and finally, the possibilities and nature of social change are discussed . How do families of one class replace another? What is the role of life cycle in social or spatial mobility? The results: an overview The findings emphasize the complexity of the household movement process and the difficulties in describing it, let alone analysing the causal forces. The definitions of the sample and the rules for exclusion of households control the findings from the start. A particularly important decision is the focus on relocation, rather than on the evolution of households and household stock. Throughout the study it becomes evident that the resultant movement matrix can not be satisfactorily discussed without reference to alterations in the housing stock and the creation and dissolution of new households. The description of the full relocation matrix reveals the high degree of integration of the Toronto housing market. Some form of migration stream links virtually every location. There are no sharp boundaries or barriers to movement. Only with considerable difficulty are migration subsystems identified and these large regions still permit 30 to 40 per cent of the movements originating within

4

them to end outside their boundaries. However, the expected bias of distance decay, outward flow, and sectoral concentration could be identified. When the movement of particular household types is examined more striking patterns of spatial bias appear. As the flow matrices are disaggregated favoured migration streams are identified, and measures of differences among the matrices calculated. Household size and the occupations of household heads are particularly effective measures. The over-all movement matrix should be viewed as an aggregate of these household subsets, each responsive to its own particular pattern of origins and opportunities. Attempts to describe the aggregate pattern in terms of other variables are not very successful. Zone size and the distance between zones is modestly effective, but measures of social distance and social interaction are virtually useless. It is evident that the location of a new home is a rather uncertain phenomenon, not readily predicted from the data available. The application of Markov chain analyses reveals one aspect of this uncertainty - the transience of the movement process as the environment, particularly housing opportunities, evolves. The relocation process cannot be comprehended in itself; it must be linked to other urban processes . THE TORONTO CONTEXT

The study area is the Municipality of Metropolitan Toronto, a grouping of municipalities which was created by the Province of Ontarion in 1953 in order to plan and develop the rapidly growing Toronto urban area. As Figure I .I

r·---------·---------------------

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Figure 1.1 The study area. Shading indicates built up area 1964. Inner region is City of Toronto, surrounded in turn by Metro Toronto and the Census Metropolitan Area.

5

Ethnic Origin

Age 100

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British/~es

15 - 34

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8I

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1851

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'11

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'31

'51

1971

Rote

Q

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100 k

'91

'11

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'51

'71

Figure 1.2 Toronto: growth and change, 185 1-1971 indicates 'Metro' is now almost completely built-up and the most rapid growth is taking place beyond its boundaries. In 1964, when the data for this study were . gathered, its boundaries coincided roughly with the urbanized area.

1851-1971 The history of Toronto is one of continuous rapid growth, fed by high rates of immigration from the rest of Canada and abroad. 1 The essentials of this development sequence are indicated in Figure 1.2. A continuous growth rate has been accompanied by gradual shifts in the composition of the population. Waves of in-migrants from other parts of Canada and abroad, combined with high rates of The standard sources on the growth of the Toronto area are Kerr and Spelt ( 1973); Simmons and Bourne (1972). Recent social patterns and changes are described by Murdie (1969).

6

natural increases, have been the long-term bases of growth. At present Toronto absorbs one quarter to one third of Canada's immigrants from abroad. The impact of immigration is particularly striking during the last decade because the immigrants differ sharply in character from the traditional Toronto stock, although there is evidence that the degree of social change was just as great in the latter decades of the nineteenth century (Goheen 1970). Since Toronto established its dominance over the rest of the province in the early part of the nineteenth century, the economy has remained much the same, but has expanded as the region has grown. Government, institutions, financial and administrative offices, wholesaling, retailing, and consumer-oriented manufacturing are the basic activities. Toronto's relationship with the rest of Ontario economy and landscape grows stronger and it is slowly wresting from Montreal the remaining Canadian hinterland outside the Province of Quebec. The rapid growth pattern has, if anything, been accelerated in the past two decades (Figure 1.3). 2 As the highest order place within the English-speaking portion of Canada, Toronto has absorbed a major portion of the economy's growth. The corporate headquarters, the media services, the research and development groups which serve the nation, are clustered here. With continued immigration, demographic, ethnic and religious differences have steadily become more complex. 3 The city has recently become more Catholic and more Latin. Various ethnic groups are now of sufficient size to create cities with the city - an estimated 400,000 persons of Italian origin inhabit a complete sector of the city from the core to the northwest suburbs; a parallel sector contains 100,000 Jews, and other areas house 50,000 Greeks and nearly as many Portuguese. Each of these sub-cities, and there are many others, contains its own commercial core, theatres, institutions, and social structure.

Recent components of growth Although the long-term growth profiles for Toronto described above are quite regular, actual growth rates fluctuate widely from year to year. (Figure 1.3). Metropolitan growth reflects broad cyclical changes in international, national and provincial economic conditions, but it actually takes place by means of innumerable individual decisions, based on people's knowledge of the present and perception of the future. Developers build, entrepreneurs invest, families 2 Recent data on Metro Toronto is found in a series of Census reports (Canada, Dominion Bureau of Statistics 1954) Bulletin CT-6, "Toronto: Population and Housing Characteristics by Census Tracts" (Canada, Dominion Bureau of Statistics 1964) Bulletin CT-15, "Toronto: Population and Housing Characteristics by Census Tracts", and Bulletin CX-1 , "Migration Fertility and Income by Census Tracts" (Canada, Dominion Bureau of Statistics 1968) Bulletin C-20, "Toronto: Population Characteristics by Census Tracts." Tables in Chapter I are developed from these matrices unless otherwise indicated. 3 Details on the ethnic patterns are given by Richmond (1967; 1972).

7

ex,

20,000

Housing starts

Apts. Rawhauses, etc.

10,000

Single Family

150,000

100,000

' 50,000

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Figure 1.3 Recent components of growth: Toronto

1960

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1969

1970

have more children, and finally the government reacts with the provision of new services, but any of these decisions can be accelerated or delayed over time producing wide variations in the amount of growth from one year to the next. Of all the components of Toronto's growth natural increase is the most stable. Although currently adding about 30,000 persons to the Census Metropolitan Area each year, recently the rate of increase, as elsewhere, has slackened. Natural increase per 1000 has dropped from I 7.7 in 1960 to 9. 7 in 1969 in the province . To this is added net migration , which in Toronto has ranged from 15,000 to nearly 60,000 persons per year during the last decade, averaging around 30,000 but displaying a distinct cyclical behaviour. The net growth by migration is largely a result of in-migration from abroad with flows of native Canadians approximately in balance . These migration cycles are integrated in complex ways with the other development cycles characteristic of a growing metropolis. Net migration is a response to the creation of new jobs, generally lagging behind the latter by about a year. Approximately 12 to 18 months after population growth occurs through in-migration, the housing stock is altered as new units are begun. Somewhat later, the public sector responds with additional social services. Finally the political boundaries themselves are altered. The length of the time lag involved, and the nature of the development response, of course, are modified by national trends in interest rates and employment - the high rate of interest in 1969 /70 and of unemployment in 1970/71 are obvious examples. As each development decision contains the possibilities for subsequent growth it becomes apparent that certain major decisions and certain boom years have considerable long term implications. In each of the years 1963 and 1967 for instance, the annual population increase was equal to 5 per cent of the existing population, and the volume of new housing construction equivalent to nearly 7 per cent of the existing stock. Clearly, individual perceptions of the future, coloured by the prevalent boom psychology, are translated into specific elements of the landscape . The housing market Demographic patterns are particularly sensitive to immediate past growth patterns, but national trends in family size and longevity are also reflected in the post-war shifts in Metro Toronto's age structure (Figure 1.4). In-migrants are predominantly young people . Toronto has strikingly high proportion of young singles and newly-weds, often employed in professional and clerical occupations and responsive to the conveniences provided in modern rental accommodation, particularly high-rise apartments. They are geographically as well as socially mobile, discriminating in their needs for services and fluid in their demand . The economy and landscape mirror their presence - the increasing diversity of occu9

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350 300 25 0 200 150 100 50

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1941

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65 515 45 35 25 15

5

65 55 45 35 25 15 5

Ago

Ago

Age

Age

1951

1956

1961

1966

Figure 1.4 Age structu re of the Metro popula tion, 1941-1966

TABLE 1.1

HOUSING DEMAND : METRO TORONTO, 1951-66

a) Household size

1951

1956

1961

1966

l person 2-3 persons 4-5 persons 6-9 persons 10+ persons

13,233 115,697 92,856 44,517 6,908

20,008 148,577 113,152 52,019 7,320

34,915 188,861 137,448 59,185 6,538

58,186 221,436 161,536 68,826 6,212

Total Households

273,211

341,076

429 ,947

516,196

b) Income Level*

$45.50

$57 .20

$63.10

$68.20

* Average wage and salary income, adjusted to 1949 dollars.

pations, of night-life and movie houses, of massive and impersonal apartment developments with built-in services, and the growing vitality of the core. Note also the tremendous growth in families with young children (Table I. I), and the eventual replenishment of the under-represented groups (the I 930s cohorts) by in-migrants during the decade 1956-66. Not peculiar to Toronto, but nonetheless significant, are continual increases in the level of real income . The latter accentuates housing demand by removing the necessity to share housing units, and allowing young people to move into their own quarters. In response to the rapid growth of the post-war period the housing stock has rapidly expanded (Table 1.2), initially by the widespread construction of new TABLE 1.2

HOUSING STOCK: METRO TORONTO, 1951-66*

Single detached Semi-detached, duplexes Apartments, flats

1951

1956

1961

1966

142,385 (52.l %)

-

268,984 (55.7)

299,508 (50.4)

84,876 (17 .6)

95,429 (16.3)

-

128,680 (26. 7)

195,207 (33.3)

341,076 (100.0)

482,540 (100.0)

586,581 (100.0)

70,486 (25.8%) not available 60,340 (22.l %) 273,211 (100.0)

* Occupied dwellings

single family dwellings in the suburban areas, aided by a variety of government incentives; and later by the addition of thousands of high-rise apartment units. The first blocks of apartments were built on sites within the central city, but soon they were rising in all parts of the metropolitan area (Bourne 1968). Despite the rapidity of construction the interaction of these demand and supply conditions augmented by international trends in inflation and interest 11

$ J0,000

Average price of properties sold through

Toronto Real Estate Boord Price detoted by the Consumers Price Index

( 1953 = 100.0) $25,000

C "'

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$20,000

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1965

1967

1969

Yeor

Figure 1.5 Average price of Metro housing rates generated rapidly increasing housing costs for single-family units during the '60s (Figure 1.5) culminating in a widely proclaimed housing 'crisis' towards the end of the decade .4 The rapid rate and source of in-migration and the nature of the economy have important implications for the nature of housing demand, but perhaps the most striking characteristic which distinguishes Toronto from most other North American cities is the continuing attraction of the central city as a residential environment. Its population has increased slightly as innumerable high-rise apartments have replaced older single-family or detached dwellings. PATTERNS OF SOCIAL CHANGE

The continuous pulse of growth originating in the city's core - the entry point for many of the in-migrants from both Canada and abroad - has led to wide4 See, for instance, the Hellyer report (Canada, Federal Task Force on Housing and Urban Development 1969) which assumes that a crisis exists; and the Lithwick report (Lithwick 1971) which rejects the idea entirely . Hellyer is a politician; Lithwick is an economist.

12

1971

spread social adjustment. The high proportions of young in-migrants and of immigrants from southern Europe, in particular, have substantially and permanently modified the traditional social geography of the city. Most changes in social patterns are linked to alterations in the housing market. The dominant area of net population increase is at the edge of the urbanized area where the traditional patterns of suburban housing construction are carried on. Within the built-up area, major demographic shifts occur when apartments replace single family dwellings. Other changes occur through the ebb-and-flow of social groups within the existing housing stock, as groups of different income, life cycle and ethnicity invade and occupy another neighbourhood. Neighbourhood transitions are the result of differential population growth, as well as the differential filtering of units of the housing stock - a process which in Toronto has some unusual dimensions. As is commonly the case, the dominant expression of this process is the filtering down of older houses to groups of increasingly lower income. Yet apartment construction has added as many as 5000 new units a year to the aging housing stock of the central city; demolitions have removed over 1000 units yearly on the average; and many hundreds of older houses have filtered upwards because of the growth of a middle class population which seems to prefer central townhouse living, and through the handyman efforts of immigrant families. As a result, the quality of inner-city residential areas has actually improved appreciably.

Murdie 's factorial ecology Despite social diversity and rapid change, the underlying geometry of social areas in Toronto is similar to that of most North American cities. For example, in his cross-sectional factorial ecology of metropolitan Toronto based on the 1961 census, Murdie (I 969) finds that communities can be arrayed on the basis of six independent and additive factors: 1, socio-economic status; 2, family status (urbanization); 3, Italian ethnic status; 4, Jewish ethnic status; 5, areas of recent growth; and 6, household characteristics and service employment. Most of these patterns are common to other cities: the first factor displays concentric zonation, the second a sectoral pattern, and the others are smaller scale nucleations often described by sociologists as reflecting social segregation. The specificity of Toronto's social ecology is represented in two ways: the separation of what is usually a single composite ethnic dimension into two factors, Italians and Jews; and the separation of some residential areas solely by their recent and rapid growth. More revealing of Toronto's changing character, however, is the analysis of social change (Figure 1.6), from analyses based on a set of relative change quotients describing proportional shifts in the socio-economic attributes of census tracts in Toronto over the ten-year period 1951-61. These quotients are defined as the ratio of the 1961 proportion to the 195 l proportion for each variable or characteristic in each tract. 13

-

----------,

~

I I I I I I I

~/

Metropolitan Toronto MILES

~

Figure 1.6 Patterns of social change: 1951-1961. Areas of potential social change as identified by Murdie's factor analysis

~

la

I. Areas of Greatest Populotion Growth 2. Areas of Greatest Ethnicity Chan9e 3. Increased Apartment Owellin9

As expected, peripheral growth is the most dominant and regular feature. Population increases in a concentric pattern around the city core, that is, in the outer development ring identified above. Values range from negative population change (at the core) to increases of 100 per cent or more. Rapid population increases at the edge of the urbanized area are accompanied by other social changes. The demographic structure shifts towards higher proportions of young adults and small children, and the transition from a rural to an urban population usually results in an upgrading of the average housing quality and mean household income. The second pattern of change emphasizes increasing ethnic segregation in the housing market. In particular, the pattern identifies the expansion of southern European ethnic groups in one specific sector of the city . The northwest sector of the city is isolated as a separate dimension by obvious changes in social attributes: the area has become more Catholic and more Italian, with a higher proportion of workers employed as labourers, with relatively low educational levels and with some overcrowding of the housing stock. Other sectors, identified at the opposite end of the scale, have become more British and more Protestant by contrast. A notable feature of this pattern is the rapid and widespread extension of the Italian sector into the suburbs and fringe. Other ethnicity shifts in Toronto are masked by the simple geographical polarity of this expression of social change. A third cluster of variables describes increases in those characteristics commonly identified by sociologists as 'urbanization' - in this instance measured by increasingly higher proportions of single adults; female participation in the labour force; few children, and predominantly apartment-living. These variables appear as isolated nodes, usually indicating major apartment developments, and principally located in a wide band around the central core, on ravine and riverbank sites, and around subway stations. Interestingly, this pattern is identified using 1951-61 change data, which predate the major high-rise apartment boom of the 1960s. The fourth type of social change, which like the first is also concentric in form, is the only one that does not imply the actual relocation of families. In Toronto it identifies a ring of housing - just inside the zone of suburban growth - where families settle down, grow older, and raise their children . Most suburbs enter this phase about ten years after development, and the phase continues until redevelopment occurs, or a new social group moves in, or both. THE STRUCTURE OF THE STUDY

The area under study in this report, then, is a rapidly growing metropolis, which has some unique features yet in most ways is typical of large North American cities. The following chapters describe recent patterns of residential relocation in 15

Toronto. First the current state of the arts is reviewed - again drawing on information about Toronto, followed by a discussion of the main data set. The over-all matrix of residential moves is presented and analysed, before moving on to studies of particular subsets of households. Finally two further kinds of analyses are attempted - first, the development of simple regression models to predict household movement, and secondly, a series of stochastic models.

16

II

The conceptual background

Before plunging into the main data source it will be useful to review existing knowledge about intra-urban residential movement. These are the theoretical constructs and empirical benchmarks against which the study data will be compared. Particular attention is paid to other data available for the Toronto area. Materials relating to analytical problems will be discussed in later sections. An earlier appraisal of the literature (Simmons 1968) identifies three approaches to the study of intra-urban migration: who moves, why do they move, and there do they move? 1 Although discussions of the movement process may integrate these approaches as Brown and Moore (I 970) have recently done, most empirical studies can be categorized into one or another of these groups. WHO MOVES?

The evaluation of migration rates is the best-known aspect of residential movement studies . It is possible to specify in great detail the proportions of different populations who have moved during a given time period. Since the census-taking institutions have become involved with the measurement of mobility the data are relatively standardized and trustworthy, but several sources of confusion remain. The first is the necessity to specify the length of study period. Annual rates of mobility (proportion of population which has changed residence) An explosion of literature in this area has occurred since the completion of the appraisal (Simmons 1968). More recent overviews include the annotated bibliographies by Welch (1970; 1971) and Chamberlain and Crowley (1970). Moore (1972) provides an even more recent summary.

17

average about 20 per cent of the population, but five year rates only about 50 per cent, since the latter do not reveal repeated moves during the time interval . Only rates measured over the same time interval can be compared directly. Of particular concern in the analysis of spatial patterns of mobility is whether the rates refer to in-migrants or out-migrants. If the question is phrased 'Have you moved?' and asked at the end of the time period, areas of recent growth such as new suburbs appear to contain a very mobile population. In fact, the residents of these communities are quite unlikely to move in the next time period, and, if observed over a further interval of time, will exhibit very low rates of movement. If the question is phrased 'Do you intend to move?,' or if movers are linked to the population to which they belonged at the beginning of the study period, the patterns are quite different. Mobility rates of the latter type are highest near the core of the city where the demographic structure and tenancy characteristics are most conducive to high rates of movement. The selection of spatial units of origin also permits the definition of a wide variety of migration rates as Table 2.1 indicates. The population of Toronto TABLE 2.1

IN-MIGRANTS TO METRO TORONTO, 1956-61 (1000s) Population (1961)

Total population, 5 years and over stayers movers from Toronto CMA from central city from suburbs outside Toronto CMA from Ontario other Provinces abroad

Percentage

1,400 .0 616.9 783.1 559.3 241.7 317.6 223.8 58.4 37.4 128.0

100.0 44.1 55 .9 100.0 39.9 71.4 17.2 30.9 22.7 39.5 16.0 28.6 100.0 4.2 7.5 26.1 2.7 4.8 16.7 9.1 16.3 57.2

contains stayers, and movers from abroad - the immigrant - and migrants from other parts of Canada, as well as from various parts of the city. The latter make up by far the greatest proportion of movers. Over 70 per cent of the in-movers to Metro residences have moved from other parts of the same labour shed . An idea of the definitional problems as well as the temporal variation in the movement rate is provided by Freedman ( I 96 7) who obtained data from Bell Canada on the number of residential phones connected and disconnected each year. The figures approximate household additions and deletions with the addition of a secular increase due to increased income legels. For Metro Toronto the proportion of moving households (number of residential phones connected) is approximately 30 per cent per year, varying between 26 .4 and 31 .7 per cent. The rate of out-movers is about 6 per cent lower, ranging from 20.4 to 26.2 per

18

~

0

~

30

.;

a.

In - Movement

C: "' ·;

0

;:!!:

Out - Movement

20

"'

-0

0

.c.

Q)

"'0:,

::C

10

i: ., u

.;

a.

0+--------.-------.--------,--1957

1960

1963

1966

Year Source

FrP.edmon, Appendix II

Figure 2.1 Migration rates over time (Metro Toronto) cent, with a high degree of correlation between the two . Freedman's other analyses, based on spatial and temporal disaggregation, show regular annual fluctuations in mobility and a predictable sequence of spatial shifts in mobility rates as the city grows.

The dominance of the life cycle The data available on migration rates indicates the overwhelming dominance of life cycle stage as a determinant of migration at all spatial levels, but particularly the intra-urban. Age, household size, and tenure - the main surrogates for life cycle - are the best predictors of the movement probability (Maisel 1966). Table 2.2 and Figure 2.2 confirm this generalization for Metro Toronto. Mobility is highly peaked for age groups 15-30 (at beginning of movement period) for both male and female . In Metro, in fact, this population - only 39 per cent of the total - accounts for over 51 per cent of the moves. Male and female rates are quite similar, although the latter lead the former by about five years. More general studies of migration have demonstrated that the propensity to move declines as the duration of residence in a particular house increases. Presumably the network of local contacts increases with time and the continuing residence indicates Jack of negative feelings about the environment. McGinnis 19

TABLE 2.2 MOBILITY RATES BY AGE AND SEX Per cent Movers, Toronto Census Metropolitan Area, 1956-61 *

Age (1961)

MALE Movers

5-14 15-19 20-24 25-29 30-34 35-44 45-64 65+

54 .2 46.3 69 .8 84.6 76.5 59 .7 41.6 31.5

Within CMA 39.6 29.6 38.7 54 .6 54.2 43.7 33.0 27 .0

FEMALE Movers

54.3 50.8 80.4 83 .5 69 .5 45.8 40.8 34.4

Within CMA 39.7 33.3 46.l 53.4 48.8 39.7 31.9 28.8

TOTAL Movers

54.2 48.5 75 .3 84 .0 73.0 52.8 41.3 32.8

Within CMA 39.6 31.4 42 .5 54 .0 52.5 41.7 32 .5 28 .1

* The Toronto Census Metropolitan Area is comprised of Metro plus a surrounding ring of Townships. Its population (l 961) was 1,824,000 compared to 1,595,000 for Metro. The data came from unpublished tables provided by the Dominion Bureau of Statistics.

(1968) has generalized this propensity into the axiom of cumulative inertia which has been demonstrated for migration at various scales (Morrison 1967; Land 1969). Evidence for intra-urban moves , however, shows that this relationship is indistinguishable from the life cycle effect (Butler et al. 1969, p. 59); and Speare (1970) shows that duration of residence has little effect on the mobility of home-owning households. %

90

BO

70

60

."'

50

>

0

::;;

40

i:

u"'

.

30

Total

a.

Some Municipality

Some Province Some Country

Age in 1961

Figure 2.2 Migration rates by age (Ontario urban residents, 1956-1961) 20

There is little evidence that occupation or other social class characteristics affect migration rates to any extent, but low income families tend to move shorter distances than upper class households. As a result the ratios of within zone moves, and within labour shed moves will be greater for the former. This generalization should be modified in part for Toronto, though. Large numbers of immigrants from abroad are included among the movers, but despite the length of their moves, their incomes tend to be among the lowest in the city. Tenure, however, may be slightly associated with social class, as well as with life cycle; and it can be shown (Butler et al. 1969, p. 59) that even with life cycle removed, tenure is a significant predictor of mobility .

Spatial patterns of migration rates The spatial distribution of mobility rates within a metropolitan area reflects the distribution of the demographic and household characteristics associated with movement. In-migration ratios, in particular, reflect the patterns of household and environmental opportunities. The proportion of in-migrants from abroad is almost exactly correlated with the location of the pre-existing foreign born population. In-migrants from other provinces of Canada are found in all parts of Metro reflecting the distribution of housing opportunities but in-migrants from other parts of Ontario - more knowledgeable and better off - are found mainly in the high-income sectors of the city. The pattern of intra-urban mobility (based on in-migration rates) shown for Toronto in Figure 2.3 is representative of most metropolitan areas (Moore 1969, in Brisbane). The inner city - highly 'urbanized' in the terminology of social

7

\ \

i I

i

407

I \I

)

/ 40

Figure 2.3 Rates of in-movement from within the Toronto Census Metropolitan Area, 19 S6-1961 (per cent of residents) 21

area analysis, with high concentration of young single people, elderly roomers, and small rental units - exhibits the highest mobility rates. The likelihood of having moved declines with distance from the core and then increases as the zone of most recent growth is reached. Almost all the residents of these areas, of course, have moved in the last five years. The overwhelming impression, though, is of uniformly high rates of movement. Nowhere in Metro can tracts be identified where less than 35 per cent of the persons have moved, and the mean value is over 50 per cent. A steady tum-over of population takes place everywhere, creating the possibility of social change in every neighbourhood . Stability of the ecological pattern occurs only because in-movers' households generally resemble out-movers, or rather, what the out-movers were like when they first came to the area. WHY DO THEY MOVE?

The bulk of recent research in residential relocation has been devoted to the motivation for changing residence because of its implications for planning and housing models oriented to prediction.2 What conditions in the household and its environment lead to relocation - and how is a new home chosen?

The Brown-Moore model The most comprehensive discussion of the movement decision is found in the Brown and Moore (I 970) paper which combines the decision to move and the location search into a single extended process of adjustment to stress. 3 Passage through the life cycle creates stress on an individual or household. The household compensates by adjustment at the existing location or by movement into a more satisfactory environment. The model is worth summarizing in some detail because of the useful terminology which it introduces. The process begins (Figure 2.4) with the household subjected to stress, coming from two time-dependent sources - the internal change in the family structure due to life cycle or socio-economic changes which make the house or the wider environment unsuitable, and the external changes in the neighbourhood which can make the location unsuitable to the household. The major sources of stress are within the household. The stress is converted to behavioural adjustments, called strain, by the household according to its personal reaction to stress. Operationally stress is defined as the difference between the need set ( defined by the household) and the environment set. Strain is the resulting 2 Among the diverse studies of movement motivation are Werthman, Mandel and Dienstfrey (1965); Michelson (1970); and Butler, Sabagh, and Van Arsdol (1964). 3 The paper by Brown and Moore (1970) draws substantially from two papers by Wolpert (1965; 1966). A more general statement is provided by Golant's (197 l) formal model for spatial interaction of all kinds.

22

External Forces: Environment (Characteristics) of Present Location: Neighborhood, Dwelling, and Relative Location in Urban Space

Internal Forces: Needs and Expectations of Household

Phase I: The Decision To Seek a New Dwelling

Place Utility at Present Loca\ion in Time T

Stress-Strain Conversion

Strain

Decision: Seek Other Residential Location for Time T+l, T+2etc.

Phase II: The Relocation Decision

Available Vacancies: Choose Advertising Media

Decision: Remain in Present Location

-

Define Aspirations for New Dwelling

Search Information Sources for Dwelling Vacancies

Examine Vacancies

Place Utility Not Improved:° Revise Aspirations

Match Vacancy Characteristics To Aspirations

Place Utility Improved: Decision To Change Residence

Figure 2.4 A model of the residential location decision process.* * Figure reproduced from L.A. Brown and E.G. Moore, "The intra-urban migration

process: a perspective." Geografiska Anna/er Series B, Vol 52B, No 1 (1970) as reprinted in L.S. Bourne (1971)

23

alteration of the need set or the environment set, taking place in situ or requiring movement. Each type of strain adjustment requires a threshold stress . Once the decision to eliminate stress by relocation is made, the need set must be made explicit in the form of an aspiration region, a multidimensional set of attribute bounds within which a satisfactory new residence must be found. Each dwelling alternative must have each element in its attribute vector within the upper limit and lower limit which defines the aspiration region. The aspiration region may be subdivided by ranking variables in importance, by subdividing each variable into categories, or by evaluating subjectively the probability of satisfying a given category of a given variable. Experience modifies the aspiration region . Too many satisfactory alternatives imply that the region is too large: insufficient alternatives may require it to be extended. Certain variables, like cost, are more likely than others to be used in these adjustments. The model devotes considerable effort to defining the search procedure by which vacancies are discovered and evaluated. Three main components of the process emerge from the discussion: the criteria set up by the household, the existence and distribution of housing vacancies, and the awareness of those vacancies by the household concerned. Housing alternatives must successfully penetrate each of these sorting devices in order to be both evaluated by and acceptable to the household. The search for housing vacancies begins with the household awareness space, formed by its activity space (daily movements) and its indirect contact space (media and personal contacts). As the search process begins the search space is a subset of the awareness space, but after the initial explorations it expands rapidly. The early experiences modify probabilities of success and alter the aspiration region; and given a time constraint, the expansion of the search space may be accelerated by changing information channels. For instance, an earlier preference of informal 'driving and looking' and talks with friends may be replaced by intensive search with a real estate agent. Werthman, Mandel, and Dienstfrey (1965) stress that shopping for a new home - like selection of a partner in marriage - is not so much a comparison of alternatives but a succession of trials. Finally a decision is made: an acceptable residence is found, either the most acceptable of those evaluated , or the only satisfactory one available at a given time; alternatively the family abandons the search and reconciles itself to the original dwelling. The search process as described by Brown and Moore (1970) is quite compatible with the theme of 'self-selection' developed by urban sociologists such as Bell (1968) and Michelson (I 969), in which the household chooses a residence (within its budget) which suits its life style. Bell (I 968) goes on to develop a typology of life styles or typical clusters of attributes, each of which can be translated into housing and locational requirements (Michelson, Belgue, and Stewart 1972). The three suggested styles are 'familism' (an emphasis on child

24

raising and family life), 'careerism' (an emphasis on one's job), and 'consumerism' (an emphasis on consumption). Some empirical evidence Two major studies, focussing on the residential relocation process, complement the description given above. A series of papers by John B. Lansing and his associates at the Michigan Survey Research Center (Lansing 1966; Lansing and Mueller 1964; Lansing and Barth 1964; Lansing and Hendricks 1967; Lansing, Clifton, and Morgan 1969) are concerned with the implications of residential choice motives for transportation planning. Their work is followed by a national survey examining the impact of residential movement on urban planning in general conducted by the Department of Urban and Regional Planning at the University of North Carolina (Butler et al. 1969). These publications contain dozens of tables describing variations in residential preference and search procedures for urban America in the '60s. Perhaps the most significant finding from these studies concerns the complexity of the process. Although all households may go through the same sequence of procedures, the characteristics of the households, their aspirations, and their decisions vary widely. Only with the greatest hesitancy can one generalize from the findings, but some consistent features do emerge. Some have been discussed in the previous section ('who moves?') and in earlier writings (Simmons 1968), but will be repeated here. Any model of urban residential movement must be consistent with the following relationships:

1 Propensity to move is primarily related to age of household head and household size . Young, growing families are most likely to move (Lansing and Mueller 1964, p. 19). Life cycle characteristics also determine the choice of housing (Lansing, Clifton, and Morgan 1969, pp. 36 ff). 2 Most moving households report a desire for increased space as the major reason for moving. The ratio of increases to decreases in space (and costs) as a result of moves, is two to one (Butler et al. 1969, p . I 5; Lansing and Mueller I 964, p. 23). Degree of present housing satisfaction is an important predictor of future mobility (Butler, Sabagh, and Van Arsdol 1964). 3 The other household attribute which leads to increased movement is tenure. Renters (at all life cycle stages) are more likely to move - and to move into rental housing (Butler et al. 1969, p. 1O; Lansing and Mueller 1964, p . I 9). 4 The North Carolina Study stresses the household's perception of its present neighbourhood as an important factor in predicting possible future moves. This sensitivity to neighbours and neighbourhood quality is, however, largely found among older households which are less likely to move (Butler et al I 969, pp. 57, 64). 25

5 Social class and life style (consumption patterns) (Bell 1968) are not related to movement rates, but do affect the final locations. 6 Accessibility of any kind is relatively unimportant to the decision to move and the decision where to relocate (Butler et al . 1969, p. 54). Lansing and Barth (1964, p. 24), in fact, found a clear reference for lowered accessibility to the city as a whole. Michelson, Belgue, and Stewart (1972) suggest that intercity migrants are more sensitive to job and over-all city access . 7 The overwhelming preferences, in terms of future locations, are for a desirable neighbourhood over the quality of housing unit , or its accessibility; for good schools over low taxes; for inside rather than outside features in a house; single floor housing; large lots; and few children in the neighbourhood (Butler et al 1969, p. 24). Wives are slightly more sensitive to housing condition; husbands worry (a lot more than wives) about financing and ,access to work (Michelson, Belgue, and Stewart 1972). 8 The imperfections of the market are suggested by some dissatisfaction with the search (30 to 40 per cent of households did not feel that they looked at the full range of suitable housing) and the number of alternatives seriously considered (less than half the households seriously considered another housing unit) (Butler et al. 1969, p. 41). 9 Eighty-eight per cent of movers are, however, satisfied with their final dwelling (Butler et al. 1969 p. 19). WHERE DO THEY MOVE ?

The major part of this study focuses on this question, thus presenting a great many opportunities to explore the current states of knowledge. Using the terminology of Brown and Moore (1970) the movement vectors are determined by the location of the opportunity space - the distribution of acceptable vacancies, as defined by the household aspirations - as it is modified by the awareness space and the search space. Given even a modestly efficient searoh procedure the opportunity space becomes dominant. Housing opportunities in a rapidly growing city are of two kinds: those vacated by other moving households - perhaps IO per cent of the housing stock per year (many moves do not leave vacancies) - and net additions to the housing stock of up to 6 or 7 per cent of the existing stock annually . The opportunities can be classified in a wide variety of ways in order to specify housing submarkets, but in general families tend to move between similar housing units similar in terms of size, tenure, or value. And, within an urban area, similar housing units are clustered in space so that a high degree of spatial autocorrelation exists among housing opportunities, however defined (Figure 2.5). The most powerful bias in the relationship between origins and destinations, is

26

• •• • • • .;: .. •

..

•

•

•

• • ••

•• • •

.• •

•

•

Single Detotched Housing ( 1966)

e •

500 units

100

Figure 2.Sa Distributions of housing opportunities - single detached

Number of houses before 1920 ( 1961) •

1000

•

200

Figure 2.Sb Distributions of housing opportunities - before I 920

27

Tracts with Median House Value

> 25,000 ( 1961)

Figure 2.Sc Distributions of housing opportunities - median house value

distance. 4 A large proportion of moves are within the zones of measurement and the number of moves declines rapidly with distance (Simmons 1968). The considerable importance of housing opportunities in determining movement patterns, hence social change, leads naturally into the literature on housing. Future efforts to model residential movements and their implications must build in concepts of filtering, redevelopment cycles, demand cross-elasticities, vacancy chains, and the like. 5 Although the significance of the housing market is recognized here, the focus on the movement pattern in this study has not permitted it to be examined in any depth. It will, however, be increasingly evident that new housing stock determines the changes in residential movement patterns. Net additions to the housing stock on the urban periphery, plus the tendency ~f families to move outward, purchasing more space as they move through the life cycle, create a marked outward bias to the migration field, as movement probability isopleths are skewed towards the periphery, and the major vectors of movement are towards the outskirts of the city (see Figure 2.6). The distribution of housing opportunities, however, is filtered by the knowledge and preferences of the consumer (the awareness space). Adams (I 969) develops this theme in some detail in his study of Minneapolis. Knowledge, at least in the initial stages of search, is related to the awareness space, which in 4 The notion of bias in a network of contacts is developed by Rapoport (1957 ; 1963). It is extended to the study of urban phenomena by Brown (1968) and Simmons (1970b). 5 The major compendium of housing theory is that of Smith (1970). Berridge (1971) has written an excellent review of the spatial implications in the Toronto context.

28

a

b

The spatial auto correlation of opportunities

C

The effect al urban growth •

The sectoral bias

Origin

Isopleths contain the cumulative probability of location

Figure 2.6 The bias of migration fields turn is linked to the action space, the locations made familiar by regular trip patterns. These patterns are largely confined to the sectors defined by the city core and the original residence of the mover, and this is particularly true in Toronto with its strong central core. Toronto also has clearly identified ethnic and social class sectors which affect household aspirations. 6 A sectoral preference should also emerge from the distribution of housing stock, since the quality of housing varies sectorally (Murdie 1969). The varieties of sectoral bias are discussed in detail by Moore (l 972). The spatial biases of distance, outward growth, and sectoral preference should predominate in a study of residential change. In addition one might expect a certain degree of reciprocity - flow in one direction should be largely matched by the return flow. Where this is not true some kind of social change is taking place . (In one of the few measures of this symmetry, Johnston (I 969b) finds a correlation of 0 .63 between flows to and from London, England .) At the same time the great diversity of households, of motives for moving, and of opportunity distributions generates virtually all combinations of movement origins and destinations. Residential relocation is an extremely complex phenomenon. Perhaps this complexity is best shown when migrant lifelines (Brown and Holmes I 97 I) are studied. The data to be presented in this study do not permit the analysis of a particular household's sequence of moves, but an abortive complementary study briefly examines these phenomena (Simmons and Hardy 1968). Figure 2.7 suggests the complexities of the results. Residents arrive in a particular community by diverse routes . Any notion of an ordered sequence of moves from A to B must, of necessity, be an artificial statistical construct. 6 Differences between the search space of the Italian and Jewish families presently living in the same neighbourhood in Central Toronto have been clearly shown by Gad, Peddie and Punter (1973). The former seek alternatives in the Northwest suburban area; the latter opt for more urban locations, usually within the North Toronto axis.

29

Figure 2.7 Migration life lines* * The open circle indicates final (l 968) destination for all individuals. The black dots show their earlier residence's location The composition of migration streams In the older parts of the city social change takes place, not by net additions of population, but the differing composition of in-movers and out-movers to an area . Following Stone (1971, p. I I), a migration stream may be defined as the aggregate of movers from a given origin to a specific destination, and the subject of investigation is the variation in composition (in terms of social class, ethnicity, life cycle stage, etc.) among streams. Stone further discusses the main source of variation in composition among migrant streams : differences in the social characteristics of the origin population in the selectivity of the movement process (as discussed earlier in this chapter), and , of course , in the perceived (by the migrant) characteristics of the destination . Very little empirical work has been done on this problem within the city and the hypotheses come mainly from studies of observed changes in social structure such as that by Murdie (1969) described in chapter I. Young family-oriented households move outward. Upwardly mobile families seek out high-income sectors. Italians move within Italian areas. Nowhere , however, is there a general model for anticipating social change in an area, or a statement of the expected

30

symmetry of flows, or of the sequence of moves by a social group. Stone ( 1971 , p. 13) does suggest the likelihood that absolute values of migrant flows of various types will be strongly correlated because of the common spatial units ( usually of considerable range) from which they arise . Large zones generate large numbers of migrants of all kinds. One approach to the study of the composition of migration streams is to disaggregate the total flow matrix and observe independently the movement patterns of the rich, the poor, the old, and the young, etc. Alternatively, indices can be developed to indicate the composition of any aggregate migration stream in the system . Both approaches will be attempted in the chapters to follow.

31

III

The data source

As so often happens, this study was initiated through the sudden availability of a body of useful data. 1 Acting on a suggestion by transportation consultant Hans Blumenfeld, the Metropolitan Toronto and Region Transportation Study (MTARTS) incorporated into its home interview questionnaire a series of questions about residential relocation. The size and quality control of the sample, and the linkages between movement information, household characteristics and trip data, present a unique opportunity to study a significant urban process . This chapter outlines the characteristics of the data set, compares the sample to other information about the population of Metro Toronto, and presents some of the basic attributes of the moving population. METROPOLITAN TORONTO AND REGION TRANSPORTATION STUDY

In I 962 the Ontario government established a committee to determine a transportation policy for Metropolitan Toronto and the surrounding municipalities. The committee, in turn, set up the Metropolitan Toronto and Region Transportation Study (MT ARTS) which undertook analyses and prepared proposals for a region including Toronto, Oshawa, Barrie, Guelph and Hamilton The initiation of the study, the financing, the acquisition of the data set and the refinement and evaluation of the sample were all carried out by Alan Baker. This chapter is based largely on his notes and comments.

32

Oshawa

Lake

Ontario

10

20

30

Mlle

Figure 3.1 The

MTARTS

study area

(see Figure 3.1), culminating in a series of final reports released in 1967.2 An important data input to this study was the Home Interview Survey, undertaken throughout the region in the spring of 1964, and conducted jointly by MTARTS and the Metropolitan Toronto Planning Board. Over 24,000 households were interviewed about their daily trip patterns, and the sampling was designed to produce estimates of total daily trip patterns for the entire region. For the purpose of studying residential relocation, only those households within Metro Toronto, about 13,000 in number, are examined. The literature on intra-urban moves indicates that patterns and reasons for moving are much 2 For a complete list of MT ARTS studies consult Ontario Department of Municipal Affairs, Community Planning Branch (1968).

33

different for moves going outside the labour shed - even to nearby towns. 3 Also there are difficulties in using census data outside Metro, where census tracts become unsatisfactory spatial units and are no longer coincident with the traffic zones used in the sample design. Each sampled household responded to a set of five questionnaires: 4 I a household report lists members of the household, age, sex, occupation, and type of industry. 2 the household facts report - filled in by the head of household - describes the residence, the former residence, the time of move and the reasons for selecting the residence . 3 trip reports were filled out for each trip by each person in the family. 4 a detailed report of the journey to work was completed for each trip of this type. 5 an administrative form was filled in by the interviewer. The coded results from these questionnaires are the primary data for this study (see Appendix). Details of the sample design The main purpose of the home interview survey is to provide estimates of daily movement by purpose and mode and time of day, within the study area. These needs determine the survey design. In rural areas the proportion of households sampled run as high as IO or even I 5 per cent. Within Metro the range is 2 to 5 per cent. For the entire survey area 3.3 per cent of households completed questionnaires. Expansion factors are provided to two decimal accuracy for each traffic zone (Traffic Research Corporation 1965). The population for the sample is a list of household provided by Ontario Hydro . A household is defined as a 'group of rooms occupied by a family or other group of persons, usually having private cooking available.' If a rooming house contains more than IO units each unit is considered to be a separate household. As Moore (1972) suggests, this is the most useful unit for the study of residential migration . Interviews were conducted by mail (22 per cent), by telephone (35 per cent), and face-to-face (42 per cent). Interviewing was checked for reliability in various ways, but particularly with respect to travel habits. The residential movement data are provided by a series of five questions in the household facts report: 3 This assumption has been confirmed by a recent analysis of the migration of households beyond the Metro boundary (Hill 1973). 4 The questionnaire is reproduced in the Traffic Research Corporation (1964) study. It follows a pattern recommended by the National (United States) Committee on Urban Transportation.

34

1 How long have you lived at this address? 2 Where did you live previously? 3 Where do you work now? 4 How long have you worked at this address? 5 Where did you work previously? Together with the present address and the household characteristics the essentials of the movement pattern are given . All locations are converted to the traffic zones used for the study. In Metro these zones correspond to the 301 1961 census tracts . The Appendix Table 1 lists the final coded data record provided for the study by MT ARTS. Note that a complete record is generated for each trip, amounting to about 300,000 records in all. The first stage in the migration analysis is the editing of the data file to provide only one trip record per household - usually the first trip taken by the first person in the household . In addition most of the trip information is deleted so that the final data tape consists of 13,316 records - one for each household -- each containing the data as shown in the Appendix, Table 2. REFINING THE SAMPLE

It is important to distinguish two kinds of population which this sample could represent. The sample was originally designed to give an unbiased description of daily trip patterns of all households in Metro Toronto. The section below demonstrates that the sample is indeed representative of the population of Metro households in 1964, but a study of residential location focuses on a different group of households, those that move within the metropolitan area within a defined time period. Propensity to move, as has been frequently demonstrated, is dependent largely on the life cycle stage of the household. If only recent movers are considered or if households are weighted by their propensity to move quite a different sample emerges. Recent movers are a biased subset of the total population, over-representing persons aged 15-30 years . The sample can be manipulated by the rejection of certain kinds of records. All households have moved at some time and have a residential origin and destination code . By considering all records the sample represents the total Metro population, but many moves will have been made a long time ago. By considering only moves made in the last year the sample represents current movement trends . At the same time over 90 per cent of the records have been thrown out. After weighing off these alternatives it was decided to restrict the sample to those households which moved during the last six years. This limits analysis to a period when the urban environment is roughly constant and centres the study period in the 1961 census (Canada Dominion Bureau of Statistics 1964) which 35

took place in June 1961, and is an important data source for many of the analyses. The moves during 1958-1964 include about 7000 records or 53 per cent of the households in the sample. The sample data which will be presented in this study, then, rperesent a compromise between a picture of the total population and a picture of the most recent movers. It should also be pointed out that only the most recent move of each of the sample households is recorded . As many as SO per cent of households in the study may have moved more than once during the study period . In similar fashion the spatial extent of the study is restricted . The initial decision to deal only with Metro households reduced the sample to 13 ,000 households out of 24,000, the decision to study only moves made during the last six years brings the number down to 7000 and the restriction of the analysis to those households which did not cross the Metro boundary eliminates another 1300. For the most part, then, the study deals with a sample of 5700 households which expands to represent a total of 203,000 household moves within Metro during the period May 1958 to May 1964. The aggregation into zones of analysis The 5700 household records, after expansion by the sample factor , represent movements among the 301 census tracts of Metro Toronto . Many of the 90,000 cells in the resultant flow matrix have no entry, presenting conceptual and technical problems of analysis and presentation. At an early stage in the analysis, two sets of aggregate units are defined . The first stage of aggregation (a level) creates 62 groups of the original tracts (with from 1 to 8 tracts per zone), with the grouping constrained to approximate equal population size and to approximate social homogeneity according to the maps in Murdie's analysis of the 1961 social patterns in Metro (Murdie 1969). As Tables 3.2 and 3.4 indicate there is still a considerable range in the size of these zones. A map of the zones is found in the Appendix. The 62 zones are further grouped into 18 larger ( c level) zones for the analyses of household subsets. These areas differ widely in size. Figure 3.2 shows how the original data is successively manipulated until the final descriptive materials emerge. Chapter 1v will focus almost entirely on the flow matrix FBI while chapter v will discuss a wide variety of the smaller 18 x 18 matrices FCl (k). An evaluation of the sample The sample is evaluated by the Traffic Research Corporation (I 965) primarily with respect to trip generation characteristics. For the purpose of this study it is useful to appraise it as a sample of households. In Table 3.1 the sample is compared to the census figures for Metro for two time periods. The first set of figures looks at household size - an apparently foolproof measure, but one which is perceived differently by different data-gathering bodies. The census

36

fA O,iginol Flow Motri• Defined by Somple ( 301 • 301 }

E1:ponded b:, Sompling Foetors

( 301 • 301)

[

'"

Aggregoted to 62 Zones Rejecting moves

-

[

fB 2

:m Ouh;de Mtt,o

re

[

Aggregoted to 18

Fat

Zones Reject moves from

Fet FC2

Moves

1958 to 1964

-t : :

FBIG

Moves before 1958

Moves

1958 -1964

fii= fii/Itii ltii tij=tq-

T'i'

j

~:tii

Iltij

,;

i'i1 = t i1 -

~ij

FBI T

fij = fijtfji

FBIN

fiJ = tij - tij

I regression

FC1 ( K) tor o voriety of household porometers

Mo11es before 1958

Outside Metro

Figure 3.2 Refining the sample gathering agency (Dominion Bureau of Statistics 1964; introduction) defines a household as 'a person or group of persons occupying one dwelling.' It usually consists of a family group, with or without lodgers, employers, etc., but it may consist of a group of unrelated persons, of two or more families sharing a dwelling, or of one person living alone. Every person is a member of some household and the number of households equals the number of occupied dwellings. The MT AR TS manual (Traffic Research Corporation I 965, p. 7) defines 'A household is a group of rooms occupied as separated living quarters by a family or other group of persons, usually housing private cooking facilities available. Domestic employees and lodgers are included, but if a rooming house has ten or more separate rooms, each is regarded as a household.' It is obvious that a certain degree of bias exists in the MTARTS sample. Small households (1-3 persons) are consistently under-represented and larger families (4-9 persons) appear too many times. The study data slightly over-emphasizes the classic North American family of Mom, Dad, and two kids seeking a home in the suburbs, tending to perpetuate the tendency of the literature to ignore the decision of the small household - the boarder, the high-rise dweller, and so on. The discussion of the results takes account of this bias. TABLE 3.1 Total number of households I person 2-3 4-5 6-9 10+

EVALUATING THE SAMPLE 1961 Census

MTARTS*

1966 Census

34,915 I 88,861 137,448 59,185 6,538

29,606 194,441 178,416 67,571 4,058

58,186 221,436 161,536 68,826 6,212

429,947

474,092

516,196

* The sample of I 3,316 households expanded appropriately. 37

TABLE 3.2

Zone l 2 3 4 5 6 7 8 9 10 11

12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44

38

EVALUATING THE SAMPLE: AREAL UNITS

Households 1961 Census 7,046 4,172 7,786 7,195 14,730 1,872 3,481 1,230 7,318 6,171 7,891 7,496 9,407 11,937 9,128 5,289 6,386 10,563 7,460 521 9,975 5,250 9,818 7,896 6,392 5,279 7,055 18,470 16,402 3,610 6,874 9,227 3,800 5,109 9,644 4,973 5,118 11,086 4,386 8,246 4,506 5,164 8,024 5,154

MT ARTS

Households 1966 Census

1958-64 movers

Within Metro movers

Movers from rest of MT ARTS*

8,666 8,903 8,780 7,618 16,551 4,150 4,328 882 9,522 7,785 11,015 6,579 10,742 13,201 14,547 5,934 6,408 10,357 7,765 782 10,034 4,980 9,993 8,155 6,365 4,932 7,138 20,605 15,919 3,916 6,652 10,742 2,996 4,732 9,223 4,761 4,798 10,890 4,305 8,410 5,664 5,305 8,166 5,254

11,336 12,098 10,043 8,496 19,596 7,902 5,002 1,319 10,436 9,432 11,779 7,850 10,905 13,899 17,619 6,333 6,911 10,690 7,693 476 10,397 5,067 10,412 9,462 6,631 4,861 7,314 21,851 17,207 3,738 8,552 11,370 3,518 4,585 9,008 4,423 4,678 11,470 4,423 9,251 6,670 5,091 7,ll6 4,807

5,934 7,529 5,444 3,837 8,714 3,350 1,792 294 7,446 4,306 5,918 2,672 4,417 4,629 12,957 3,186 2,784 3,992 3,089 338 4,150 1,669 4,528 4,125 2,302 2,716 3,466 10,593 6,594 2,549 3,896 7,377 1,705 1,996 4,238 2,315 2,434 5,897 2,000 4,435 3,396 2,946 3,642 1,674

4,698 6,016 4,370 3,190 6,837 2,550 1,504 168 6,333 3,977 4,644 2,182 3,946 4,043 9,434 2,626 2,190 2,637 2,597 292 3,786 1,461 3,898 3,220 1,938 2,460 2,556 8,343 5,609 1,989 3,060 5,886 1,367 1,500 3,599 1,759 2,017 5,168 1,650 3,771 2,620 2,500 3,156 1,546

396 498 113 36 509 0 40 158 284 144 358 91 0 49 637 100 30 43 0 0 182 63 58 79 32 0 92 136 139 37 82 142 138 86 35 0 67 49 95 77 80 31 66 0

TABLE 3.2

Zone 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 Total

continued

Households 1961 Census

MTARTS

Households 1966 Census

1958-64 movers

Within Metro movers

Movers from rest of MTARTS*

6,891 10,165 5,937 8,891 5,575 4,082 3,343 4,902 6,848 3,549 8,652 5,934 6,423 4,201 2,153 9,210 3,672 11,083

6,361 11,751 5,852 8,633 5,986 4,239 3,436 5,530 8,785 3,773 9,093 6,081 6,298 4,533 2,093 14,905 5,672 12,514

6,277 12,285 6,291 8,758 5,325 4,775 3,546 5,740 9,774 3,948 9,208 6,719 7,620 4,674 2,211 18,240 5,973 14,053

2,448 6,857 2,380 3,251 2,303 1,956 1,840 2,767 5,186 1,549 4,675 3,642 3,389 1,856 759 10,516 3,693 7,434

2,100 5,472 1,922 2,483 1,828 1,767 1,596 2,143 4,048 1,252 3,881 2,856 2,830 1,528 690 8,283 2,470 6,167

0 107 45 70 34 78 64 36 99 62 115 289 156 119 48 474 137 55

429,947

474,092

516,196

249,773

203,406

7,190

* From the non-rural centres in MT ARTS only (Hill 1971)

Table 3.2 reveals the extent to which the biases carry over to space. The sample is quite representative of all areas . If the criteria for comparison with the sample households are the number of households identified by the census in l 961 and 1966, over 60 per cent of the zones samples lie within this range (41/63). Virtually all the errors in the other zones are less than 5 per cent and they are concentrated in zones of little change where the range of values from 196 l to 1966 is very small indeed. Only two zone samples (8, 20) had errors as large as 30 per cent - both are very small (in terms of households) and very complex. The spatial pattern of the errors is non-existent - they can be considered to be purely sampling variations . The modifications to the data undertaken for this study alter the sample to a much greater extent, however. The proportion of the original sample which is actually analysed ranges from over 60 per cent in zones 2, 6, and 9 to less than 30 per cent in zones 18, 22, and 48. The average is around 40 per cent. The study of recent movers emphasizes new suburban and central city movers, while the Metro boundary restriction means that zones on the periphery of Metro are under-represented. 39

The relation between households and housing stock A final appraisal of the sample comes from the examination of the distribution of households of various types into different forms of housing stock. Table 3.3 provides a brief overview of the situation in 1964. Both family size and family income emerge as important determinants of housing type. TABLE 3.3

HOUSEHOLDS AND HOUSING STOCK Single-family

Family size l 2 3 4 5 or 6 6+ Total

7,800 50,000 50,400 71,900 77,100 19,800 277,000*

Family income in doJlars 7,900

Total

224,900*

Per cent 2.7 17.6 17.7 25.3 27.l 7.0 100 3.5 9.1 25.l 19.5 16.8 25.9 100

Other 5,900 20,900 20,900 23,900 26,900 13,000 111,500 5,200 15,500 24,700 13,900 8,900 30,800

Per cent 5.3 18.7 18.7 21.5 24.l 11.7 100 5.3 15 .7 25.0 14.0 9.0 31.4

99,000* 100

Apartments 16,300 38,900 20,200 13,200 6,500 500 95,100 5,100 13,700 21,300 11 ,300 9,100 3,400 63,900*

Per cent 17.2 40.9 21.2 13.9 6.8 0.5 100 8.0 21.5 33.4 17.7 14.2 5.3 100

* There was a considerable amount of no response to the income question. THE PATTERN OF ORIGINS AND DESTINATIONS

The various kinds of bias introduced by the method of gathering and sorting the data can be further explored by discussing their impact on some simple distributions. In this section the location of migrant origins and destinations obtained from the MTARTS data is described and compared to other data sources. The Census of Canada, 1961 (Canada Dominion Bureau of Statistics 1964), for instance, publishes extensive information on the characteristics of in-movers to each census tract during the period 1956 to 1961, and Freedman (I 967) describes the timing of household movements by area. Figure 3.3 summarizes the over-all movements in, out and within the Metro system. Since the sample is drawn at the end of the movement period, no data are available on those households who left Metro, or which break up for various reasons. The 203,400 households which are represented are assumed to exist 40

Stayers (224,300) 1958 (460,900)

Movers (236,600)

*

I

Within Zones

1964 ( 474,100)

( 45,700)

•

Within Metro . ___ Among ( 157,700) ___;;.....Zones ___ _:..._.;..__ __• ( 203,400),___

Estimated - We know that 23,200 went from Toronto to other locations within the MTARTS region

Figure 3.3 Household movements. Metro Toronto : 1958-1964 62 zones both at the beginning and end of the time period. A closed system is defined which does not grow by either net increase or net migration during the period 1958-64.

Relationships with the rest of the MT ARTS Region Before focussing entirely on the closed system it is possible to examine briefly the relationships between Metro and the immediate surrounding area. A paper by Hill (1973) examines migration patterns throughout the large MTARTS area (Figure 3.1) and some of his findings are relevant here. The region extending about 50 miles from the centre of Toronto includes about 700,000 households - compared to Metro's 450,000. The most significant finding is the high degree of net out-migration from Metro to the rest of the region . Although Metro in the early sixties was attracting a net migration of at least 10,000 households per year, this surplus includes an annual net loss of over 2,000 to its surrounding field (see Table 3 .4). The rest of the MT AR TS region, then, is largely an extension of the Toronto suburbs and draws heavily on the city as a source of growth. Net in-migration is particularly high in the zone within IO miles of Metro and weakest for the larger established cities farther away, such as Hamilton and Guelph. 41

TABLE 3.4 HOUSEHOLD MOVEMENTS BETWEEN TORONTO AND REST OF MT ARTS REGION : 1958-64 To Metro

To rest of region

Totals

Metro From rest of region

203,400 7,300

23,200 143,000

223,600 150,300

Totals

210,700

166,200

373,900

The spatial distribution of this loss within Metro is of concern because it biases the closed system analysis . The peripheral zones of Toronto have the highest rate of interchange of migrants with the larger region but only small net losses. The major areas of net loss are the older parts of the city, and also the northern end of the Yonge Street corridor which is losing people to centres farther out such as Richmond Hill . Maps of in-movement and out-movement show quite different patterns. The move to Metro from the surrounding area is not selective - migrants are likely to go anywhere in the urban area. But out-movement from the city is aligned sectorally. Movers originating in the East End of Metro tend to continue in an easterly direction . North Toronto movers go north and so forth . The residential structure of Metro is being reproduced in the urban field . Origins and destinations Within Metro itself the migration pattern is characterized by considerable imbalance (Figure 3.4). The suburban areas, rapidly adding new housing units, are experiencing absolute population growth, while the central city - where the number of housing units is relatively fixed (see chapter l) - appears to be losing population. In fact the net out-movement as shown by the sample is replaced by the creation of new households as young people move in and marry, and the migration of households from outside Metro, both from abroad and other parts of Canada. The net movement pattern, although referring only to moves within the Metro boundary, resembles those previously calculated from census data (Simmons 1972). High rates of out-migration are found at the city centre, particularly from the two lower-income sectors - east and northwest. The suburbs are consistently areas of in-migration with movement focused on two or three zones of particularly rapid growth in this period - e.g., zones 2, 9, 15, and 60. The Yonge Street corridor, which attracts large amounts of apartment construction because of its upper middle class character and subway construction, shows little net change .

42

X

• X

o,1g,ns ( su,plus)

0

1000

)(

1000 des11notions (surplus)

e

1000 of eocl'I

Figure 3.4 Origins, destinations and net movements By closing the system the results under-estimate in-migration from zones which receive many immigrants from abroad and from other parts of Canada i.e ., the inner parts of the low-income sectors. At the same time certain parts of Metro which contribute disproportionate numbers of movers to distant parts of Metro's urban field have out-migrant estimates which are too low.

Migration rates The extensive information about intra-urban migration rates has been summarized in some detail. The information contained in Table 3 .5 can be used to corroborate those generalizations. As is pointed out in Chapter II, two distinct spatial patterns of mobility rates can be generated for cities. If, at the end of the time interval, households are asked about movement a characteristically doughnut-shaped pattern is observed (Murdie 1969, p. 136). The city centre with its small households , apartments, and boarding houses is an area of high mobility, but so are the new suburban districts where entire neighbourhoods have moved in within the last five years. On the other hand a study which looks at an initial population and asks how many of these people move within a finite period, leads to a pattern with a single focus - the core of the city - similar to the distribution of the urbanization or family status dimension of social area analysis . Figure 3.5 is of the latter type. It takes as its base the households at the beginning of the study and identifies the proportion of movers. The mobility rate is the ratio of movers from zone i to the total of stayers plus movers from i. The observed range of value is 25 to 72 per cent. The pattern reveals the

43

TABLE 3.5

ZONE TOTALS

(4) (l) (2) (3) (5) (6) (7 )=(1 )+( 6) (3)x100 InWithin- (5)x100 Net Total Stayers OutTotal (l 958)* moverst (I) moverst movers (3) movers (1964)** 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43

44

5,238 2,814 6,152 6,232 12,608 1,415 3,422 989 3,456 4,211 8,198 6,906 10,104 12,595 5,779 4,600 5,703 10,877 8,908 1,505 10,749 5,954 10,190 6,891 7,719 5,218 6,363 18,701 15,902 3,579 9,580 8,435 3,775 5,931 12,817 5,525 6,020 l l ,402 4,699 8,214 4,120 5,528 8,788

2,732 1,374 3,336 3,781 7,837 800 2,536 588 2,076 3,479 5,097 3,907 6,325 8,572 1,597 2,748 3,624 6,365 4,676 444 5,884 3,311 5,465 4,030 4,063 2,216 3,672 10,012 9,325 1,367 2,756 3,365 1,291 2,736 5,085 2,446 2,364 4,993 2,305 3,975 2,268 2,359 4,524

2,506 1,440 2,816 3,451 4,771 615 886 401 1,380 1,732 3,101 2,999 3,779 4,023 4,182 1,852 2,079 4,512 4,232 1,061 4,865 2,645 4,775 2,861 3,656 3,002 2,691 8,689 6,577 2,212 6,824 5,070 2,484 3,195 7,732 3,078 3,656 6,409 2,394 4,239 1,852 3,169 4,264

52.1 51.1 45.9 55.4 37 .9 43 .5 25.9 40.4 39.9 41.l 37.9 43.4 37.4 31.8 72.5 40 .3 36.4 41.5 47.5 70 .6 45.2 44 .4 46.4 41.5 47.3 57.5 42 .2 46.4 41.3 61.8 71.3 60.l 65 .8 53.9 60.3 56.7 60.6 56.1 49.l 51.6 45.1 57.4 48 .7

4,698 6,016 4,370 3,190 6,837 2,550 1,504 168 6,333 3,977 4,644 2,182 3,946 4,043 9,434 2,626 2,190 3,637 2,597 292 3,786 1,461 3,898 3,320 1,938 2,460 2,556 8,343 4,609 1,989 3,060 5,886 1,367 1,500 3,599 1,759 2,017 5,168 1,650 3,771 2,620 2,500 3,156

808 436 631 341 1,558 100 192 0 431 274 897 526 753 736 2,162 386 204 862 899 52 1,126 275 975 507 370 1,132 568 2,379 1,528 317 1,200 2,139 650 376 1,740 523 311 1,404 210 730 328 768 1,278

32.1 30.3 22.5 9.9 32.7 16.3 21.6 0.0 31.3 15.8 28.9 17.5 19.3 18.3 51.8 20.8 9.8 l 9.1 21.2 4.9 23.2 10.4 17 .8 17 .7 10.1 37.7 21.1 27.4 23.2 14.3 17.6 42 .1 26.2 11.8 22 .5 17.0 8.5 21.9 8.8 17 .3 17.7 24.2 30.0

2,192 4,576 1,554 -261 2,066 1,935 618 -233 4,953 2,245 1,543 -827 167 20 5,252 774 111 -875 - 1,635 -769 -l ,079 -l,184 -827 359 - l ,718 -542 -135 -346 - 968 -221 -3,764 816 - l,117 -l ,695 - 4,133 - 1,319 -l,639 -l ,341 -744 -468 768 -669 - l,108

7,430 7,390 7,706 6,971 14,674 3,350 4,040 756 8,409 7,456 9,741 6,089 10,271 12,615 11,031 5,374 5,814 10,002 7,273 736 9,670 4 ,772 9,363 7,250 6,001 4,676 6,128 18,355 14 ,934 3,358 5,816 9,251 2,658 4,236 8,684 4,205 4,381 10,161 3,955 7,746 4 ,888 4,859 7,680

TABLE 3.5 continued (1) (2) (3) (4) (5) (7 )=(l )+( 6) (6) Within- (5)xl00 Net (3)xl00 InTotal Total Stayers Out(1958)* moverst movers (3) movers (1964)** moverst (I) 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62

7,182 7,788 11 ,089 8,292 10,417 6,322 4,157 3,455 4,574 5,452 3,654 8 ,990 4,880 6,363 4,137 2,065 6 ,655 3,426 10,528

3,580 3,913 4 ,894 3,472 5,382 3,683 2,283 1,596 2,763 3,599 2,224 4,418 2,439 2,909 2,677 1,344 4 ,389 1,979 5,080

3,602 3,875 6,195 4,820 4,035 2,639 1,874 1,959 1,811 1,853 1,430 3,572 2,441 3,454 1,460 721 2,266 1,447 5,448

Total 427,730 224,321 203,409

50.2 49.8 55 .9 58 .2 38.7 41.7 45 .l 56 .6 39.6 65 .8 39.2 49.1 50.l 45.6 35.3 34.9 34.0 42.2 5 l.7

1,546 2,100 5,472 1,972 2,483 1,828 1,767 1,596 2,143 4 ,048 1,252 3,881 2,856 2,830 1,528 690 8,283 2,470 6,167

248 639 1,746 570 497 243 378 408 574 408 58 943 752 1,567 350 46 891 26 2,120

203 ,409 45,721

6.9 16.5 28.2 l l.8 12.4 9.2 20.2 20 .8 31.7 22 .0 4.1 26.4 30.8 45.4 24 .0 6.4 39.3 l.8 38.9

2,056 -l,775 -723 -2,898 - l ,552 - 61 l - 107 -363 332 2,195 - 178 309 415 - 624 68 - 31 6,017 1,023 719

5,126 6,013 10,366 5,398 7,865 5,511 4 ,050 3,192 4,906 7 ,647 3,476 8,299 5 ,295 5,739 4 ,205 2,034 12 ,671 4,449 l l ,24 7

0

427 ,730

* Total 1958 is the sum of stayers and out-movers to Metro. It does not include households who relocate outside the boundary. ** Total 1964 is the sum of stayers and in-movers from Metro. It does not include household moving in from outside Metro. t 'In-movers' and 'Out-movers' each includes 'Within movers.'

expected high mobility rates in the core area dropping off to low rates in the eastern and western suburbs. More surprising is the core of high mobility rates to the Northwest - a zone of active expansion by the Italian community during this period . An even more complex pattern is shown in Figure 3.6 which portrays the proportion of movers originating from a zone who relocate within it. The values vary widely over space - a high of 51.8 per cent is adjacent to a low of 1.8 per cent - and reflect the size of unit and degree of local community attachment as well as the more general ecological pattern . The core area of very low income and the older communities of the Lakeshore and Weston stand out, but recent suburban developments also show a high rate of internal movement.

45

However simple, these distributions, identifying the basic locational structure of mover origins and destinations, play an important part in understanding the flow of households among locations. Big zones, little zones, zones of population loss or gain - each contribute to the pattern of the flow matrix.

Figure 3.5 Out-movement rates

Figure 3.6 Per cent moves within zones; per cent of out-movers who relocate in the same zone 46

IV Over-all movement patterns

This chapter describes the major patterns of residential relocation during the period 1958-64, among the 62 zones of analysis defined in chapter 111. Magnitudes of flow refer to the expanded sample . The amount of information - for 3844 separate dyads - makes cartographic or statistical generation difficult so a wide variety of techniques and parameters are applied . Figure 4.1 presents cartographically the basic matrix to be analysed (matrix FBJ). The pattern is complex. Several zones (5, 15, 28, 38, 60) participate very strongly because of their size, but many small ones, particularly in the Northwest and in the periphery, do not appear to be closely linked to the rest of Metro . As will be discussed below the map pattern reflects decisions made in the preliminary spatial aggregation and the selection of the map legend. By altering aggregation units and scales the map can be modified substantially. In general, though, the patterns hypothesized in chapter II are observed. Short-distance flows - within zones or to contiguous zones - predominate . The strength of outward movements is obvious: the inner suburbs are fed by the core , the outer suburbs by the inner suburbs. Four major migration streams can be identified, all essentially sectoral: the East End, the North End (Yonge St.), the Northwest (Dufferin St.), and the West End. Considerable flow also takes place between sectors. Zone 15, which contains Don Mills, a relatively selfcontained suburban development, draws migrants from all parts of the city . The unique aspects of the housing stock and its isolated location among the Don Valley ravines keep it apart from other sectors. 47

___,._ 1000 500 - - 300

Figure 4.1 The flow-matrix - 62 zones - number of households PROBLEMS IN PRESENTATION

Many of the early studies of flows were made possible by a variety of simplifications. Movements in or out of a single place were investigated (the innumerable studies of service areas or urban fields), or net changes at a set of points, or net movements between points. Sometimes the analysis of flows took advantage of great variations in the value of lij with the matrix F. A few major flows above a certain threshold were studied and the rest ignored. The problem here is that areal units are roughly of equal size and have been arbitrarily defined from smaller data units. Cartography The graphic display of flow matrices is difficult because of the great quantity of information they contain. 1 The flow matrix can be represented by a series of desire lines, but a matrix with more than ten states becomes unreadable since n states generate n 2 flows. A more satisfactory approach is to use two maps for each state; one showing the origin of in-flows, and the other representing the destination of out-flows, but this study would have to deal with 124 maps. If there are a substantial number of zeroes in the matrix or the matrix can be generalized by using an average value for each row or column, two maps - one One alternative is the use of an extremely fine grained flow line. The Chicago Area Transportation Study (1959) develops the cartographatron which traces each flow separately on a cathode ray tube and then summarizes them photographically. Although the overall effect is excellent it is impossible to deduce the number of movements between any two particular places.

48

for all origin fields and one for all destination fields - may be used to describe the matrix. Berry and Horton (1968, p. 43) can describe the commuting fields for all United States Metropolitan Areas on a single map because there is virtually no commuting among metropolitan areas. Wolpert (1967) represents the migration fields of all U.S. cities on a graph by using modal or median values to represent the field and transforming each field by placing each city in turn at the centre of a polar graph - plotting average distance and direction from that point.2 Within an urban area the cartographic problems are compounded by the arbitrary nature of the spatial states. Decisions about the level of spatial aggregation and of zone boundaries govern the size of zones. Once a threshold level of flow is determined for plotting, larger areas will dominate the mapped pattern . It is difficult to separate magnitude and intensity of flow without introducing into it some kind of scaling procedure. The cartographic difficulties are demonstrated when variations on Figure 4.1 are plotted. Figures 4 .2 and 4.3 map total flows ifij +lji) and net flows (lji - fij)- The former emphasizes the strength of the total linkages between locations and, presumably, those locations which have a strong reciprocal flow if;j = lj;) have similar social characteristics. The map shows a surprisingly strong pattern of radial contacts instead of the sectoral flows of Figure 4.1. Moderately strong flows are less than the threshold size for plotting when taken individually, but appear stronger than the unidirectional sectoral flows when added together. The map accentuates links between areas of similar life cycle stage, but sectoral boundaries (the Don Valley, the railway in the West End) are still important in the inner city . The map of net flows, on the other hand, emphasizes the non-reciprocal flows between zones of different life cycle stages. The unidirectional flows to growing suburban areas are shown, but the more symmetrical linkages between inner-city zones are ignored. The major lesson to be drawn from this series of maps is that the Metro Toronto residential areas are closely interlinked. There are no isolated communities observable at this scale. Scaling Many of the difficulties in generalizing and describing a flow matrix for a metropolitan area result from the use of arbitrary areal units as the basis for analysis (see also Moore 1972, p. 24) . The spatially continuous settlement of the metropolitan area is subdivided into units which are (in this analysis) roughly equal in population size and homogeneous in terms of social characteristics. But by aggregating the moves of several thousand households into a flow matrix some basic problems are created. 2 Brown and Holmes ( 1971) provide a lengthy review of techniques of vector analysis, and Moore (1970) discusses some specific applications.

49

The proportion of internal moves for each areal unit is related to the size and shape of the unit, as Kulldorff (1955) and Wendel (1957) have shown. The larger the area in both size and number of households, the fewer the moves which cross the boundary. More recently, Taylor (1971) has demonstrated that the shape of an area can contribute as much to the relation between distance and interaction as the distribution of opportunities or the costs of transportation . It is, of course, impossible to define zones which have equal area, equal population, and the same shape. Most procedures for generalizing or describing the data are sensitive to zone populations. Large zones appear as dominant nodes - they attract more of the largest outflows in a graph, more of the wide arrows on a flow map, and dominate the factor structure in a factor analysis. The designation of the areal units shapes the pattern which results. For instance Figures 4.1 , 4.2, or 4.3 could each be modified by aggregating some of the zones in the northwest portion of the map . The data used in this study present an initial problem: whether to scale on the basis of households or movers. Use of the former leads to a flow matrix which shows a great deal of movement in the suburban areas; use of the latter suggests a high rate of activity in the older parts of Metro. It seems preferable to choose movers as the significant base since it is the deviations in movement patterns which are of interest. If movers are used for scaling, the use of row or column totals (e.g. , Savage and Deutsch 1960) ignores the system boundary effects. Peripheral locations generate most of their within system linkages to a limited number of nodes which connect them to the main body of the metropolitan area . Central locations, on the other hand, send and receive movers from a large number of zones. As a result variances within the rows and columns of the flow matrix vary a great deal and scaling using mean values has unequal effects. Peripheral areas appear to have very large linkages to a limited set of nodes. Central areas appear to have weak linkages to a large number of nodes. Given a measure with which to scale an appropriate functional relationship must be selected. The usual advice (Wolpert 1969) is to analyse deviations from some basic patterns, and various transformations of the data have been suggested using magnitudes at origins and destinations, and distance. Each alternative creates its own bias in the result . In this study three alternative scaling procedures are tried out, and the effects examined. Relationships among the procedures are shown in Figure 4.4 in a bivariate analogy . The ratio scale is defined as fij = lij / 7.lij • lij), converting each flow element to a proportion of the total flow from its associated zones. As discussed above the main effect is to reverse the emphasis from large central areas to small peripheral zones (see Figure 4 .5). The over-all pattern is chaotic

(7

50

-

1000 500 300

Figure 4.2 Total flows - number of households

~soo --300

Figure 4.3 Net flows - number of households

51

I I Ratio Scale I I

Original

•12 I

•J3 flow

flow (Ii)

(11)

e2

•I' I

.14 I I

• 15 10

Size

Sizr of unit (~fl)

of unit (~Ii)

Deviation

i//

Scale

/1s,

ope

1 size 11

n

Regression Residual

/ flow (Ii)

/

J//1 Size of unit (

flow (Ii)

~

Size

f,)

of unit (~Ii)

Figure 4.4 Scaling techniques with short flows among the central city zones and long movements to the periphery. The sectoral patterns so noticeable in Figure 4.1 are no longer visible. The deviation scale is defined as:

/jj = lij - '?ij•~lij/~

1lij

From each observed flow is subtracted an expected value proportional to tlie size of flow to and from the associated zones. The output from this transformation can contain negative values, but here only the large positive scores are plotted. It is difficult to suggest a meaningful threshold value for plotting this map since the original data from the expanded sample already contains a considerable error term. In fact the mean value of lij (55) is about the same size as the sampling expansion factor (35.8). When mapped (Figure 4.6) the deviation scale emphasizes the strong outward flows to the peripheral areas, with little sense of the movements within the central city. Finally a regression residual scale is developed in which /;,j = f ij - (a+ bflij + c7fij) where a, b and c are regression parameters fitted by a least squares procedure. The equation is: 52

- - - Ratio > 5.0 , _ . . Ratio >10.0 Within Zone lmlls and Links to •s hove ~en deleted

010203040 MILfS

Figure 4.5 Ratio scale

~

500 households

-

300 households

( no within zone moves ore plotted.)

Figure 4.6 Deviation scale

53

ftj = -52.94 + 0.01614 (origins)+ 0 .01613 (destinations)

(0.00122) (0.001 IO) R =0.3034 R 2 =0.092 Obviously scale is not a major source of the variation in flows . When plotted, the residuals from this model are virtually identical with those from the deviation scale. Flows to peripheral zones are accentuated and flows to central locations appear less important. This scale has the property that row and column totals of residuals are equal to zero. It is apparent, however, that none of these scaling procedures is appropriate for a closed system of finite size. Boundary effects distort the transformation and certain aspects of the size of the original units remain. The original flow matrix is the most useful matrix for analysis. OTHER FORMS OF GENERALIZATION

Distance and direction It is hypothesized in chapter II that the main cause of the observable distance decay in urban migration fields is the spatial autocorrelation of housing opportunities. Figure 4 .7 describes the distance decay of residential moves in Metro .

.,., >

0

E

0

0

,. Distance

( Kilometres )

Figure 4.7 Residential movers by distance

54

28

"

The magnitude and regularity of decline show clearly: lij = 94.85 (distanceij) - 1.112 r = -0.436 r2 =0.190 but it should be recalled that the system boundary eliminates the possibility of moves longer than 35 kilometers, and reduces the possibility of moves proportional to distance . For the system as defined in this study the mean length of move is 5.63 km and the standard deviation is 5.63. When the vector sum of all moves is computed the whole system shifts 0.04 km to the north and 1.45 km to the west. Again by neglecting the moves across the Metro boundary the observed degree of shift is reduced . The same parameters can be calculated for each zone, with predictable results. The mean distance of moves increases regularly as origins shift from the city centre (3.6 km in zone 33) to the periphery (about 10 km for origin at the edge of Metro). The Lakeshore zones (56, 57, 58) generate and attract disproportionately short moves, however, as does the Northwest. Moves to the city centre are shorter than moves from it, but moves to the periphery are longer than moves from those zones (confirmed by Johnston 1969a). Of somewhat greater interest is the spatial distribution of the resultant movement, the vector sum of all moves.3 The pattern (Figure 4.8) appears to contradict

01020

30

40

2

il

335.0 0 .187

345 .0 0 .148 1.6

1.1

436.0 0.125 5.2

Limiting Vector E Zone

2

3

4

5

6

7

8

9

High income Low income No children Children

0.Q25 0.034 0.024 0.040

0.063 0.097 0 .069 0 .110

0.106 0.054 0.064 0.074

0.009 0.009 0.007 0.012

0.118 0.079 0.058 0.148

0.025 0.053 0.036 0.048

0.048 0.036 0.036

o.ois

0.019 0.038 0.043 0.020

0.130 0.067 0.083 0 .096

Zone

10

11

12

13

14

15

16

17

18

High income Low income No children Children

0.106 0.118 0.177 0.041

0.045 0.059 0.079 0.022

0.001 0.017 0.010 0.010

0.006 0.033 0.017 0.033

0.032 0.077 0.067 0.057

0.026 0.049 0.047 0.026

0 .034 0.042 0.049 0.026

0.032 0.044 0.034 0.045

0.205 0.082 0.100 0.156

stationary (4>2) than the low; and both of them appear less stable than the aggregate pattern. Once again sampling error may be a factor.

The Markov chain analysis: an overview With these elementary analyses completed comments can be made about the utility of these models. 1 Without a context of growth and change of opportunities in the spatial states the model has no forecasting value. A great deal of additional material on the sizable amount of household formation and attrition and external migration would also be needed. 2 The emphasis on the process itself helps stress the great instability in the relocation process. The patent unreality of the arbitrary spatial states is obvious, and the data set becomes steadily weaker as it is pushed farther back in time.

1l 3

But the most striking observation which emerges is the transience of the movement pattern. The map of moves in Toronto is valid for only a brief period, and will probably never be repeated. It can, perhaps, be argued that every moving household evaluates a different set of opportunities, as the housing stock continues to evolve; but, more significant are the broader areas of alteration. Within a few years whole new regions are created within the city and important new social boundaries emerge. 3 The difficulties enumerated above suggest that the application of the simple Markov chain to the migration data simply adds a few additional parameters for the comparison of household subset matrices. In no way should they be interpreted as forecasts of social change. 4 It is apparent that the models applied here are much too simple. If this kind of modelling is to be taken seriously the models will have to consider continuous time processes, embedded matrices of household characteristics and the like. There appear to be no shortcuts to the study of residential relocation.

114

VIII

Implications

The various analyses of household movements within Metro Toronto provide a comprehensive picture of the relocation process in a growing North American city. Although no explicit hypotheses are tested a structured preconception of movement patterns are their sources is presented (Simmons 1968 and chapter 11) which has been referred to throughout the study. Undoubtedly, though, the intricacies of particular analytical procedures prevent the reader from obtaining a clear view of the over-all pattern as it cumulates. To this end the major findings which emerge from the various analyses have been synthesized, together with an appraisal of the limitations of the study, and a brief discussion of the meaning of the findings . COMPLEXITY

Dominating every approach to the data is a sense of the complexity of the process, and the difficulties in generalizing, conceptualizing, and analysing the movement of households for an entire metropolitan area. Empirically The description of such a system, as pointed out in chapter IV, requires the summary of a very large amount of information - the several thousand elements of the flow matrix - and is rendered even more difficult by the possibility of expanding the dimensions of the flow matrix almost at will, to an ultimate size in this study of 301 x 301. Only the existence of a very powerful structure in these matrices would permit an efficient summary to be undertaken. Such a

115

structure is not readily identified . The flows are largely asymmetrical, and only modestly responsive to the friction of distance. The migration streams are usually biased strongly towards peripheral locations, but there are always significant counter streams. Although a very crude regionalization of flows can be identified, there are observable migration streams between all locations in the metropolitan area. No simple conceptual or mathematical model can capture more than a small portion of this information. The difficulties are both clarified and complicated when consideration is given to the composition of the migration streams. If the movement between two locations is treated as the sum of several different migration streams of different household types some of the complexity in FBI can be understood. Each different set of households responds in a different fashion to the space between the origin and destination and the housing opportunities in each of them. Although movement from i to j may continue strongly for one occupation group it may be obscured by increases in the reverse flow by other household types . The problem then becomes the description of several different matrices instead of one. However, only relatively unique household types - the very rich or the very poor - create flow matrices sufficiently structured to produce a high degree of prediction. Even less anticipated is the degree of variation in the flow pattern over time. As will be discussed below, the location of growth of the urban area modifies the distribution of available opportunities in each time period, but even older parts of the city generate significantly different origin and destination fields over time as the residential composition of neighbourhoods changes. Conceptually Each of the observed complexities challenges the conceptual structures with which we try to comprehend the city. The literature on urban social processes is filled with over-simplistic concepts of social change in the city, almost all of which - suburbanization, invasion, growth - are conceived in terms of observed net change. 1 How should a stable area (no observed social change) which regularly exports a surplus of households to a sequence of new suburbs be described? What is the process by which an older suburb exports the full income range of families while absorbing only blue-collar workers? Simple taxonomies and simple parameters obscure these complex processes. On the other hand an approach which views social change in a specific location as the residual of two different processes, in-movement and out-movement (or twenty processes - in and out for ten different household types), does not lead to an optimistic view of forecasting social change in the city, as will be discussed Cave (1969) and Moore (1972) have attempted to define neighbourhood typologies based on neighbourhood type and degree of net change and mobility rates.

I 16

below. In order to simplify the relationship between social change and migration some knowledge of the interaction among movement processes in an area is required. Is in-movement of one household type associated with in-movement or out-movement by another? This study is not prepared to answer this question, but it is the obvious further step in the research on social change. A continual conceptual difficulty in this study - and others - is the need to differentiate the moving population from the population as a whole. The great variations in age-specific mobility rates mean that samples of movers are largely composed of young households, and over-represent their preferences and spatial biases. The further implication, as Morrison (1971) stresses, 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. Finally, the analysis of moving households leads to a distorted perspective of the housing market. Rented accommodation - in particular, smaller places - account for a large proportion of housing opportunities at any point in time because of the high rates of turnover; yet, paradoxically, at the end of a limited time span a relatively small proportion of households may be living in these places. Once a single-family dwelling is purchased, a household is much less likely to change residence. The urban geographer will be disappointed by the weakness of distance and spatial pattern as determinants of aggregate movement patterns. In Toronto, the asymmetry of movement weakens the distance bias. The location of particular opportunities can be an effective predictor of movements, but is difficult to specify appropriately for disaggregated households. Two kinds of reality about urban space must be faced: not distance, but concentration of relevant opportunities within space (and time) govern interactions; and there is a great heterogeneity 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. Technically To an unanticipated degree the results of this study are determined by a series of analytical decisions made at early stages in the research. The latter have been discussed at length and alluded to frequently, but they cannot be overemphasized. Given the data the decisions are as reasonable as any alternative, but they do affect the outcome. The focus on the pattern of movement, rather than on social change or housing demand, isolates the analysis from various theoretical structures and prevents any intensive investigation of the determinants of movement patterns. In fact, as noted above, it can lead to misconceptions about the housing market. The decision to ignore moves across the boundary of Metro creates distortions in flow patterns and maps such as the resultant vector patterns (Figure 117

4 .8) and the mobility rates in peripheral areas. More seriously, it prevents the analysis of an important source of urban growth and future migration - the migrants to Metro from other parts of Canada and abroad. These households are spatially concentrated (Table 8.1 ), have quite specific social characteristics and, presumably, will move through the urban area in a distinct fashion . However, Hill (1973) discusses some patterns of out-movement across the boundary. TABLE 8. 1 IN-MIGRANT COMPOSITION 1956-1961 * (Simple correlation coefficients, 301 census tracts) Variable

l 2 3 4 5 6 7

Movers/population over 5 Within Canada movers/movers Within CMA/movers Within city/within CMA Outside CMA/movers Same Province/movers Abroad/movers

l.000 0.973 0.813 0.150 0.535 0.350 0.542

2

3

4

5

6

7

l.000 0.793 0.062 0.542 0 .375 0.371

l.000 0.145 0.462 0.423 0.358

l.000 0.081 0.153 0.368

l.000 0.310 0.250

1.000 0.063

1.000

* Data from Canada, Dominion Bureau of Statistics, Census of Canada I 961, Bulletin CX-1. The effects of choosing a particular time period have been debated at length. The longer the period studied, the fuzzier the picture of a transient process. The shorter the time, the less relevant the picture is to notions of social change. Similarly the scale, the size variation, and the shape of spatial units of analysis presents unavoidable difficulties to the analyst. The results are specific to the spatial units selected, but attempts have been made to probe their stability and to compare alternative sets of units . The effects of aggregation decisions also plague the discussions of the behaviour of household subsets. As the sample size increases the sampling error is reduced and the matrices are more dependable. At the same time the amount of variation among them is decreased - they resemble the aggregate pattern more and more . Forty to fifty per cent of the variance in flow patterns at this scale is derived from the common variation in zone size. URBAN GROWTH

The movement patterns described for Metro Toronto are undoubtedly influenced by the rapid rate of growth of the city during the study period. The rapid evolution of the movement patterns is clearly evident as is the considerable influence of new housing stock on the pattern for any one year. The impact of urban growth on the degree of social change is also significant but will be considered in the section to follow. 118

New housing: magnitude and location During the six year period of study about 102,000 new housing units were completed in Metro (see Figure 1.3), an increment amount to 24 per cent of the 1961 housing stock. In the same period of time this study identifies 203,000 household movements within Toronto, not all of which created vacancies because of new family formation and undoubling. Many (uncounted) repeat moves took place as well during the study period, but the vacancies and opportunities created approximately cancel out. The implication is that new housing plays 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 (Figure 8.1). 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 characteristics of new housing opportunities At any point in time or location in space an influx of new housing may dominate certain aspects of the housing market and profoundly alter the movement pattern. As Grigsby (1963) and Lansing, Clifton, and Morgan (I 969), have demonstrated the inter-relationships among the various sectors of the housing market are not well defined, but some conjunctions can be made about the particular role of new housing in the movement process.

.. ...... ..

Figure 8.1 Housing changes, 1956-1966 119

The supply of new housing in Toronto during the study period is 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 differently 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 (see Table 8.2). 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 . TABLE 8.2

NEW HOUSING AND MOBILITY

Older housing New apartments New houses

Out-mobility

In-mobility

Vacancies created/ Out-migrant

medium high low

low high high

low high high

Vacancies created/ In-migrant medium low high

New apartments (see Bourne 1967), 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 generate far more future movers. At any one point in time, then, new housing accounts for a large proportion of the opportunities available to prospective movers, creating a considerable spatial bias in the pattern of destinations available. Moreover the lumpiness of new housing developments in Toronto - frequently of the order of 1000 dwellings, either high-rise or single family - means that the spatial bias a few months later may be equally strong, but in a different location. The nature of the housing constructed determines whether or not the location will begin to send out a steady stream of future movers and future opportunities. Two quite different matrices can be hypothesized (they cannot be measured in this study). The pattern of moves to second-hand housing is stable with the conventional types of biases as put forth in chapter 11. The pattern of moves to new housing, however, changes very rapidly over time and probably draws movers from a much wider area of the city. The sum of these two matrices is what is observed. The new housing market also affects the attractiveness of older housing. To a certain extent old and new housing can be substituted. Older apartments downtown reflect the cost of new apartment alternatives. The slight variations in cost between development alternatives due to all the institutional constraints on the 120

housing market - capital markets, public subsidies, land use controls, etc. - can lead to considerable short-term variations in the options available to a household with a given budget. Presumably in the long-run the family gets what it wants in some form, but the move to the suburbs may be indefinitely delayed by the relative disparity in downtown high-rise and suburban single-family prices.2

Evolution of movement patterns Accompanying the spatial sequence of new housing location is the extremely regular evolution of the spatial distribution of demographic characteristics (Murdie 1969, and in particular Simmons 1973). A tremendous surge of young people, aged 15-25, 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 Toronto Metropolitan area. This evolving spatial demography, together with highly localized patterns of new housing leads to movement patterns for Toronto which change rapidly over time. Different points in time and different lengths of time present markedly different flow matrices for analysis. FBI and the parameters which describe it can only be interpreted as indicators specific to the study period. These interdependencies make it difficult to model the sequence of flow matrices without reference to the evolution of the urban area in which they take place. Obviously the trend is towards dispersal of the population, and increased participation of peripheral zones in the movement process. The result is a less structured flow matrix, as the parameters in Table 5.8 indicate. Some trends specific to Toronto are the increase in the effect of sectoral boundaries in the older parts of the city over time, while boundaries at the fringe of the urban area appear blurred and diffused. The social characteristics of newer residential neighbourhoods are not clearly defined and they tend to draw in-movers from all sections of the city, as well as from outside Metro. SOCIAL CHANGE

The significance of intra-urban migration in the understanding of social change within neighbourhoods is 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 2 Derkowski (1971) shows that single-family housing costs have increased about twice as fast as income levels and apartment rents between 1961 and 1970, and that housing of this type is now much less accessible to Metro families than it was in the SO's.

121

spatio-temporal pattern of residential land use. And the new housing market, as is frequently stated (e.g., Grigsby 1963, p. 187; White 1971, p. 92) 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 is possible to gain some ideas of the trends in social class shifts.

Sources of social change The reasons for changing social patterns in the city are many and diverse. The starting point 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 housing requirements. Social change is the modification of the map of these characteristics, and can occur through changes in the national level, by the growth of the 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 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 reflect national trends in fertility, marriage, and increases in real income. The high rates of depopulation of large parts of the older area of Toronto as young households leave, is due primarily to 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 of certain social groups by migration or differential rates of increase. Toronto has been characterized by increases in the proportions of residents with Italians and other Mediterranean origins and young people (Figure 1.2). 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 . In Metro Toronto the pattern of social change reflects primarily the differentials in the relative rates of growth of social groups. The patterns which vary sectorally - ethnicity and social class - simply expand at the edge of the urban area with minor adjustments of the sectoral boundaries. The main source of change is the continuing high rate of net migration of young households into the 122

core of the city, which creates a series of waves of life-cycle shifts outward from the city centre . Life cycle changes The pattern of moves by various sizes of households is shown in Figure 5.2; young households live around the urban area and after the birth of one or two children, move outward to the suburbs. The spatial pattern of net migration by

~, ,r

r- ---:::;i..----

\ I

I , I

Figure 8.2a Patterns of net migration - 0 - 4

. 9 olnoflOOOper10na

•

9olnof lOOper,on1

0 Ion ol 100 p1r.on1

Metropolitan Toronto

Figure 8 .2b Patterns of net migration - 15 - 19 123

Net Ml9rallon,1961-1966 l>qa Gn,up 25-29 • tolftof to0pefl0ftl O loN of K>O pertont

Metropolitan Toronto

Figure 8.2c Patterns of net migration - 25 - 29 age groups are much clearer (Simmons 1973) with very regular distributions, varying strongly for different age groups (Figure 8 .2). The main zones of life cycle change are the expansion of the young in-migrant areas in the area as apartments are built, the ageing 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. These are the most powerful aspects of social change, as well as the most powerful forces behind residential relocation. They are responsible for 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.

Changing social class As indicated in the discussion of Figures 5.3 and 5.4 it is difficult 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 middle and upper class sectors (Figure 6.4). The expansion of different social class groups has been largely accommodated by the extension of their long-established sectors and 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 is quite similar - the range between the $30,000 and $50,000 new home (1960s prices!). 124

Actual transitions of older areas 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 iron') of small streets of poor housing in the North Yonge sector, or the insertion of 'young professional' apartments in similar areas. Ethnic characteristics have been frequently referred to despite the lack of data, drawing from a general knowledge of social change in Toronto. It seems reasonable to infer from the composition of origin and destination areas that certain migration streams are largely Italian or Jewish. The flow pattern maps and observed migration streams (Figure 4.10) appear to confirm intuitive feelings about the role of ethnicity in differentiating residential sectors of the city, although the relationship with social characteristic indicators (chapter VI) is very weak. What is not known is the behaviour of minoity groups in areas of ethnic change, or the lagged response of certain ethnic groups to other groups. THE COMMUNITY

Finally, this study poses some fundamental questions about the nature of the community in the spatial sense. There is repeated evidence that at this point in time and for this scale of analysis, households are not tightly bound in space, but frequently make major changes in their urban environments, apparently with little stress (see also Simmons 1973). Individuals and families move throughout the Metropolitan area as their housing and access requirements are altered, and participate in the activities of several different neighbourhoods in their lifetime . The facility with which these changes are made is explained in part by the recent work of Wellman et al. (1971), also undertaken in Toronto. Their data show that the network of contacts, activities, and support for individuals are widely dispersed in space, with some of the strongest linkages even taking place outside the Metropolitan area, by means of telephone. Households move to satisfy their particular housing requirements defined by the life cycle, while maintaining their various contacts with friends, relatives, and workplace in all parts of the city by means of the easy accessibility of the Metropolis. These findings support the notions of Webber (1964) about 'non-place' communities within the city, and they also suggest a variety of further policy and research questions: 1 Households can apparently easily survive the major environment changes which they undertake. Do they prefer this life-cycle segregation or are they driven to it by the exigencies of the housing market? 2 Since virtually every family is a potential future resident of every area, it could be argued that they should participate in decisions about the area which may affect them: that the present resident of a neighbourhood should not necessarily have more control over the space than the future or past residents. 125

3 Are there households which attach a great significance to a spatial community? If so can they be identified and their migration streams studied? 4 ls the observed lack of community continuity related to the rapid growth of the city and the resultant intensity of life cycle change? The questions raised in this section lead to the over-all theme of this chapter: the close relationship between the movement pattern 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 of any one type without understanding the choices in type and cost of housing which are open to them. The spatial pattern of residential moves is very much a by-product of the operation of the housing market.

126

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134

Appendix The original records n = 300,000 The basic unit on the output tape file is the trip record . There is a record written for each trip recorded in the home interview survey. Each trip record contains not only all the information pertaining to the individual trip but also all of the information pertaining to the trip maker and his household . In many cases there are persons living in surveyed dwelling units who made no trips or trips unknown during the survey day . The data relating to these persons and their households are, nevertheless, recorded as trip records on the tape file. They differ from the real trip records by a 2 or 3 code in column 2S of the record, which indicates that no trips or trips unknown were made, and by the fact that there will be zeros whenever information pertaining to a trip is relevant. Certain of the fields on the trip record pertain to the head of the household only, the work trip only, a car driver only , or a transit rider only. When these fields are not relevant to a particular trip they will be recorded as "zero." Trip record format

a) First card image Field

Zone number Sample number Person number Trip number Number of persons living here Number of persons < S years age Number of servants, roomers Number of passenger cars Number of company or leased cars Number of trucks Sex Age

Driver's license Did you make trip?

Column number

1-S 6-8 9, 10 11,12 13,14 1S,16 17 ,18 19 20 21 22 23 24 2S

Field

Column number

Occupation Industry Trip day Number of wage earners Total household trips Origin zone Destination zone Departure time Minutes walked at start Arrival time Minutes walked at end Type of property at trip end Purpose from Purpose to Travel mode Number of transfers

26,27 28 29,30 31 ,32 33,34 3S-39 40-44 4S-48 49 ,S0 S 1-S4 SS,S6 S7 S8 S9 60 61 13S

Field

Column number

Number of persons in car Type of parking Duration of parking Parking charge

62 63 64-67 68-71

Method of payment Type of residence

1-5

13 14 15 16 17 18 19 20 21 22 23 24 25 26-29 30-34 35-39 40-43

Where worked previously Household income Car driver questions: Car necessary for work Travel time by car Time saved Time lost Travel cost by car Money saved Money lost Convenience Long walk to bus stop Minutes walked at trip start Minutes walked at trip end Long wait at bus stop Minutes wait at bus stop Too many transfers Number of transfers Ride by public transportation uncomfortable Others Blank Logical record part number(2)

1-5 Zone number 6-8 Sample number 9,10 Person number 11,12 Trip number Car driver questions: Shortest travel time by route 13 14 Shortest travel distance

Traffic free flowing Enjoy scenery Necessary to serve passenger Other Transit rider questions: Do not own car Do not have driver's license

Field

Column number 72

73 74-79 Logical record part number (l) 80

Blank

b} Second card image

Zone number Sample number Person number Trip number Importance of selection of residence: Good price or rent Neighbourhood Easy to get to by road Easy by public transport Quality of schools Near to schools Near to parks Near to work Near to local shopping Near to shopping centre Near to friends and family Near to church Other How long lived here Where lived previously Where work now How long worked here

6-8 9,10 11,12

44-48 49 50 51 52,53 54,55 56 57-59 60-62 63 64 65,66 67,68 69 70,71 72

73 74 75 76-79 80

c) Third card image

136

15

16 17 18

19 20

Column Field number Car used by others 21 Travel time by public transportation 22 Time saved 23,24 Time lost 25,26 Travel cost by public transportation 27 Money saved 28-30 Money lost 31-33 Safety 34 More convenient 35 Long walk from parking lot 36 Minutes walk from parking lot 37,38 The rewritten records Variable number

2 3 4 5 6 7 8 9 10 11

12 13 14

15 16 17 18 19

Width 3 2 2 2 2 2

2 2 4 3 2 2 3 2 2

Field Others Shortest travel time by route Shortest travel distance Prefer to ride subway Seat available Fewest transfers Frequent service Scenery Other reason Blank Expansion factor (zonal) Expansion factor (trip) Type of interview Logical record part number (3)

Column number 39 40 41 42 43 44 45 46 47 48-68 69-73* 74-78* 79 80

il = 13,316

Location 1-3 4,5 6,7 8,9 10,11 12,13 14 15 16 17,18 19,20 21 22-25 26-28 29,30 31,32 33-35 36,37 38,39

Description Tract number B Zone number C Zone number Number of residents Residents < 5 Servants, roomers Number of cars Company or leased cars Trucks Number of wage earners Total household trips Type of residence How long lived here Where lived previously (tract) Where lived previously (zone B) Where lived previously (zone C) Where work now (tract) Where work now (zone B) Where work now (zone C)

* Fixed Point Format

137

Variable number

20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45

138

Width

Location

Description

4 3 2 2

40-43 44-46 47,48 49,50 51 52 53 54 55 56 57,58 59 60,61 62 63 64 65 66 67 68 69 70 71

How long worked here Where worked previously (tract) Where worked previously (zone B) Where worked previously (zone C) Household income Car necessary for work Sex Age Driver's license Did you make trip Occupation Industry Trip day Selection of residence Selection of residence Selection of residence Selection of residence Selection of residence Selection of residence Selection of residence Selection of residence Selection of residence Selection of residence Selection of residence Selection of residence Selection of residence

I

2 I

2

72

73 74