Household Indebtedness and Socio-Spatial Polarization among Immigrant and Visible Minority Neighbourhoods in

Canada’s Global Cities

by

Dylan Simone

A thesis submitted in conformity with the requirements for the degree of Master of Arts

Department of Geography and Program in Planning University of Toronto

© Copyright by Dylan Simone 2014

ii

Household Indebtedness and Socio-Spatial Polarization among

Immigrant and Visible Minority Neighbourhoods in Canada’s

Global Cities

Dylan Simone

Master of Arts

Department of Geography and Program in Planning University of Toronto

2014

Abstract Two key attributes of contemporary global capitalism are on the one hand, financialization and

rising household indebtedness, and on the other, high levels of mobility and migration between

nations, particularly into the ‘global’ cities. Studies on household debt as it relates to race and

immigrant status are scarce outside of the US. This thesis investigates levels and types of

household indebtedness at the neighbourhood scale among immigrant communities and areas

containing more racialized people, in the three largest Canadian cities – Toronto, Montreal, and

Vancouver (TMV). In particular, it seeks to understand whether racialized and immigrant

neighbourhoods experience higher and more onerous kinds of debt (such as unsecured forms of

consumer debt) than other neighbourhoods, and the contours of any correlations between them.

Descriptive statistics and regression models demonstrate that neighbourhoods housing immigrant

groups, and certain visible minority groups, relate to higher levels of unsecured consumer debts

in TMV.

iii

Acknowledgments

There are a number of acknowledgements I would like to make, for those who have aided me in

my completion of this MA thesis. First, I thank Alan Walks for being a magnificent supervisor.

The amount of effort and time you have dedicated to help me succeed over the past year can

hardly be quantified, and I am both privileged and proud to be able to work with you over the

next four years as I embark on my PhD. I would second like to thank my committee members,

Deb Cowen and Jason Hackworth, for their insight, comments, and comradely criticisms.

I would like to thank Bruce Newbold and Richard Harris for continuing to be exemplary mentors

as I continue my academic career. I appreciate all the help and suggestions you have both

provided over the years, and look forward to the new challenges and opportunities presented on

the road ahead.

The Department of Geography and Program in Planning at the University of Toronto, and the

Department of Geography at the University of Toronto Mississauga have provided support

(financial and otherwise) over this past year, particularly around helping fund the dissemination

of this thesis research at various conferences.

My friends and colleagues at Massey College have provided an infinite source of intellectual

inquiry, deep friendship, and, at times, comic relief. I am grateful to know the Fellows at this

College, and cannot put into words my appreciation of the institution – for its financial support,

and boundless opportunities for intellectual engagement and growth.

The Royal Canadian Geographic Society provided funding, through their Maxwell Human

Geography Scholarship, and I am very thankful for the financial support.

Finally, I would like to thank my grandparents for teaching me the importance of family, and my

mother, for being an endless source of support and love throughout the progression of my

academic career. I therefore dedicate this thesis to the Miller family.

iv

Table of Contents

 

ACKNOWLEDGMENTS  ......................................................................................................................................  III  

TABLE  OF  CONTENTS  ........................................................................................................................................  IV  

LIST  OF  TABLES  ....................................................................................................................................................  V  

LIST  OF  FIGURES  .................................................................................................................................................  VI  

1   INTRODUCTION  ............................................................................................................................................  1  1.1   CHAPTER  OUTLINE  ........................................................................................................................................................  9  

2   FINANCIALIZATION,  HOUSEHOLD  DEBT,  AND  THEORIES  OF  INEQUALITY:  A  LITERATURE  

REVIEW  .................................................................................................................................................................  10  2.1   FINANCIALIZATION,  INNOVATION,  AND  THE  GFC  ................................................................................................  10  2.2   HOUSEHOLD  DEBT  IN  AN  INTERNATIONAL  CONTEXT  .........................................................................................  13  2.3   THE  CONTEMPORARY  CANADIAN  DEBTSCAPE  .....................................................................................................  15  2.4   THEORIZING  FINANCIALIZATION,  DEBT,  AND  NEIGHBOURHOODS:  CLASS  MONOPOLY  RENT  .....................  20  2.5   CANNIBALISTIC  CAPITALISM  AND  THE  DEBTFARE  STATE  ..................................................................................  22  2.6   PONZI  NEOLIBERALISM  .............................................................................................................................................  24  

3   DATA  AND  METHODS  ................................................................................................................................  27  3.1   DATA  .............................................................................................................................................................................  27  3.2   METHODS  .....................................................................................................................................................................  30  

4   RESULTS:  HOUSEHOLD  DEBT,  IMMIGRANT  RECEPTION  NEIGHBOURHOODS  AND  

RACIALIZED  COMMUNITIES  ...........................................................................................................................  32  4.1   DESCRIPTIVE  RESULTS  ..............................................................................................................................................  32  4.1.1   Metropolitan-­‐level  ..............................................................................................................................................  32  4.1.2   Spatial  Distribution  of  Household  Debt  at  the  Neighbourhood-­‐level  ..........................................  35  4.1.3   Levels  and  Types  of  Household  Debt  in  Immigrant  and  Visible  Minority  Neighbourhoods41  4.1.4   Multivariate  Results:  OLS  Regression  Models  for  Canada’s  Global  Cities  ..................................  50  

5   DISCUSSION  AND  CONCLUSION  ..............................................................................................................  60  

REFERENCES  ........................................................................................................................................................  69  

v

List of Tables

Table 1. Total Household Debt as a Percent of Annual Income By Urban Region, 2012 …….. 34

Table 2. Composition of Household Debt, By Urban Region, 2012 ………………………….. 35

Table 3. Toronto Descriptive Statistics ………………………………………………………... 43

Table 4. Montreal Descriptive Statistics ………………………………………………………. 44

Table 5. Vancouver Descriptive Statistics …………………………………………………….. 45

Table 6. Quartiles, Toronto, 2012 ……………………………………………………………... 46

Table 7. Quartiles, Montreal, 2012 ……………………………………………………………. 47

Table 8. Quartiles, Vancouver, 2012 …………………………………………………………... 47

Table 9. Toronto Correlations …………………………………………………………………. 49

Table 10. Montreal Correlations ………………………………………………………………. 49

Table 11. Vancouver Correlations …………………………………………………………….. 50

Table 12. Neighbourhood-Level OLS Regressions, Toronto, 2012 ………………………….. 54

Table 13. Neighbourhood-Level OLS Regressions, Montreal, 2012 ………………………….. 56

Table 14. Neighbourhood-Level OLS Regressions, Vancouver, 2012 ………………………... 58

vi

List of Figures

Figure 1: Banks Profiting from Newcomers ……………………………………………………. 8

Figure 2: Housing Prices, Canada and the United States, 1999-2014 ………………………… 17

Figure 3: Household debt as a percent of disposable income, Toronto, 2012 ………………… 37

Figure 4: Location quotient for household debt as a percent of disposable income, Toronto,

2012 …………………………………………………………………………………………...... 38

Figure 5: Household debt as a percent of disposable income, Montreal, 2012 ……………...... 39

Figure 6: Location quotient for household debt as a percent of disposable income, Montreal,

2012 …………………………………………………………………………………………….. 39

Figure 7: Household debt as a percent of disposable income, Vancouver, 2012 ……………... 40

Figure 8: Location quotient for household debt as a percent of disposable income, Vancouver,

2012 …………………………………………………………………………………………….. 41

1

1 Introduction Canada is growing more unequal and polarized, at a faster rate than most advanced industrial

societies, and in doing so is becoming more like the United States and Britain (OECD 2011). In

terms of income, the gini coefficient of inequality between families has grown 3.3 percent in

Canada, 1.8 percent in the United States, and 0.9 percent in the UK between the mid-1990s and

mid-2000s (OECD 2011). For Canada at the household level, the gini coefficient has grown from

0.379 in 1981 to 0.433 in 2006. At the level of the nation-state, in 2006 the gini coefficient was

0.324 for Canada, 0.378 for the US, and 0.345 for the UK – showing Canada’s rising inequality

over the past decades (OECD 2011). These trends are similar at the urban scale, as income

inequality and polarization has increased steadily in Canadian cities since the mid-1980s (Walks

2013a). This is true not only among families and households, but also among places – among

different municipalities, and neighbourhoods (Ibid.).

The rise in inequality is not only articulated in greater dispersions of income, but in other

variables as well. One important variable often overlooked by contemporary researchers is the

level of indebtedness, and the burden that this places on individuals, families and households, as

well as on places containing highly indebted households. When debt and debt service rises faster

than income, it reduces quality of life and the ability to consume. This is particularly important,

given that the level of indebtedness, and the rate of interest charged on different kinds of debt,

changes often. One cannot thus ascertain wellbeing from income alone. One must take into

account debt and debt service.

Households have, over the past thirty or so years, been forced to take on debt to gain access to

basic life necessities – such as housing, health care, and education – in light of stagnant middle-

class wages, the privatization of most public goods, and other neoliberal tendencies

(Montgomerie 2006, 2009; dos Santos 2009; Lapavitsas 2009; Lysandrou 2011). In this sense,

household debt has seen such a sharp increase not because of recklessness on part of households,

but rather, to maintain a basic, dignified, quality of life and standard of living. Despite this,

critical scholarship into household debt is seriously lacking, especially in regards to small scales

(below the nation state), vulnerable populations (immigrants, racialized minorities) and across

time.

2

Recently, the Global Financial Crisis (GFC) brought to mainstream attention the growing

polarization of society, highlighting the growth of the “1%”. Much of this growth is tied to the

financial sector, through processes of financialization – referring to the growing importance and

influence of finance and finance capital within economies (Krippner 2005; Epstein 2005).

Financial risk and financial ‘innovations’ were fundamental to the global financial crisis. Many

of these innovations were designed to hedge against, distribute, and profit upon risk

(Montgomerie 2006, 2009; Lapavitsas 2009; Walks 2010; 2013). Two key drivers of innovation

in the recent field of so-called ‘structured finance’ (Fabozzi 2001; Hurst 2001; Wyly et al. 2006)

were securitization and risk-based pricing. Securitization – the process by which financial

institutions package debt obligations and sell them to investors – encouraged the growth of

subprime and predatory lending, given the lenders who created the loans did not have to bear the

risk; securities sold to investors (often globally) would take on the risk of these loans (Aalbers

2008; Ashton 2009; Sassen 2009). While securitization began with residential mortgages in the

1970s United States, it did not stay confined to this realm: automobiles, credit cards, pawn shops,

etc., allowed the creation of asset-backed securities (ABS), while those focused on mortgages

typically were packaged into mortgage-backed securities (MBS) (Caskey 1994, 2005; Karger

2005; Marron 2009).

Financial innovation and financialization in Canadian society are related to the restructuring of

mortgage markets and new mortgage insurance products, as well as to the rapid expansion of

payday lending through most of Canada in the 1990s and 2000s. The securitization of mortgages

began in 1987, but it was not until the development of the Canada Mortgage Bonds (CMB)

program in 2001 that as large of a proportion of mortgages came to be securitized (Walks 2014).

The Canada Mortgage Bonds program sold non-amortizing CMBs to investors, and used the

proceeds to buy mortgage-backed securities from Canadian lenders. This was done through a

‘special purpose trust’ operated by the CMHC (called the Canada Housing Trust), and operated

in a similar fashion to that of the ‘off-balance sheet’ special purpose vehicles used in the US; in

short, the Canada Housing Trust moved mortgages off the banks’ books, thus lowering the

required amount of capital needed on site via the Basel requirements. This then allowed them to

originate more mortgages that could then be sold to the Canada Housing Trust. Prior to the

Mortgage Bonds program, the CMHC merely guaranteed mortgage lenders’ interest and

principal in case of borrower default (Walks 2014). Through the 2000s, a range of new mortgage

3

products and mortgage insurance products facilitated greater leverage among borrowers. Such

mortgage products include “cash-back” mortgages in which banks are allowed to “gift” the down

payment and/or offer mortgages with loan-to-value ratios greater than 100 percent. Mortgage

insurance innovations include the “self-employment recognition” mortgages in which lenders

accept at face value what self-employed borrowers claim as their annual income without

documentation. One result has been a run-up in levels of indebtedness. In Canada, household

debt more than doubled since 1986 (Walks 2013b). From the 1960s to the 1980s, Canadian

households carried debts around 65 percent of their disposable income; by the end of 2012, the

average Canadian household carried debts at 222 percent of their disposable income –

representing an increase of 350 percent. This shift is unparalleled in Canadian history, and can be

viewed broadly as a result of financialization.

Given the magnitude of the GFC’s reverberations, scholarly literature studying the ways in

which households are unevenly impacted by the GFC has been abundant, with significant

attention being paid to the ways in which race, visible minority, and immigration statuses

alleviate (or exacerbate) this growing inequality (Aalbers 2008, 2009; Crump et al. 2008; Darden

and Wyly 2010; Dymski 2010; Forrest and Yip 2011; Wyly et al. 2006, 2009).

While predatory lending has been prominent in the US since the dawn of financial deregulation

in the 1980s (Manning 2000; Sullivan et al. 2000; Renuart 2004; Squires 2004; Immergluck

2009; Ross and Squires 2011), particular financial innovations in subprime mortgages in the era

of ‘structured finance’, such as prepayment penalties, teaser rates, and balloon payments were

vital to the GFC, and the resulting foreclosure crisis (Quercia et al. 2007; Immergluck 2011;

Ding et al. 2011; Engel and McCoy 2011). Quercia and colleagues (2007) find that even after

controlling for other factors, mortgage refinance loans in the United States with prepayment

penalties were 20 percent more likely to result in foreclosure, while those with balloon payments

were 50 percent more likely to end in foreclosure. Given the concentration of predatory loans in

racialized neighbourhoods and communities, the resulting foreclosures produced distinct spatial

patterns along class and racial lines. Ding et al. (2011) note that neighbourhoods in states with

antipredatory laws, (i.e., surrounding mortgage contract terms such as regulating prepayment

penalties, etc.) displayed lower overall default rates on mortgages, and thus had fewer

foreclosures. When looked at spatially, Immergluck (2011) shows that it is neighbourhoods in

both the city cores and suburbs that were affected by the foreclosure crisis, depending on the

4

housing market – in those cities that had a weak housing market, foreclosed neighbourhoods

were concentrated primarily in the inner city, while those cities that experienced the most

extreme housing bubbles had foreclosures concentrated in the suburbs.

Clear evidence now exists of the ubiquity of subprime and predatory loans targeting racialized

minorities in the US, in addition to these being concentrated in racial and low-income

neighbourhoods – many of which have gone from being redlined to greenlined (systematic

exclusion to systematic inclusion and predation for purposes of profit extraction) (Conley 1999;

Immergluck 2013; Niedt and Martin 2013; Rugh and Massey 2010; Taylor et al. 2004; Squires

2009; Wyly and Holloway 1999; Wyly et al. 2006, 2007, 2009; Darden and Wyly 2010;

Williams et al. 2005; Hernandez 2009). Continuing the systematic inequality and exploitation,

foreclosures were concentrated in these same communities and neighbourhoods, while at the

same time traditional banks have been replaced by increasingly shady and dubious predatory

lenders, such as payday and Money Mart lenders (Crump et al. 2008; Gerardi and Willen 2008;

Grover et al. 2008; Laderman and Reid 2008; Wyly et al. 2001; Allen 2011; Graves 2003; Smith

et al. 2008; Gallmeyer and Roberts 2009). Wyly and colleagues (2009) show that from 2004 to

2006, the percent of high-cost loans taken on by Blacks rose from 37 to 54 percent, while for

Latinos it increased from 25 to 46 percent. After controlling for other factors, Blacks and Latinos

were still twice as likely to be approved for credit compared to non-Hispanic whites. This

approval rating is amplified when these groups are concentrated in racialized metropolitan areas

and neighbourhoods, such as Cleveland and Baltimore. Niedt and Martin (2013) note that since

2007, the foreclosed in America are statistically more likely to be Latinos, reside in

neighbourhoods with social problems (such as crime, unemployment and lack of affordable

housing), while those who have ties to someone who experienced foreclosure are more likely to

report economic distress. Rugh and Massey (2010) find that segregation in metropolitan areas,

particularly for Blacks, through using measures of residential dissimilarity and spatial isolation

proved to be significant predictors of foreclosures, when investigating the top 100 American

metropolitan areas (according to measures of segregation of Blacks, Hispanics and Asians).

Allen (2011) confirms these findings, noting that amongst native-born Americans, racialized

minority households were statistically more likely than white households to experience

foreclosure for both home purchases and loan refinancing. Meanwhile, Hispanic immigrants

were more likely than non-Hispanic whites to experience foreclosure on home purchases.

5

While there is much evidence relating immigration, race and predatory/ subprime lending in the

US, as of yet, the relationship between rising indebtedness and either race or immigration status

has not received sufficient attention in Canada. This despite the high levels of immigration into

Canada’s three largest metropolitan areas (Toronto, Montreal, Vancouver), and despite the fact

that immigration and the racialization of poverty have played important and complex roles in the

production of inequality in Canada’s cities, and remain key areas requiring research surrounding

issues of social and spatial justice (Galabuzi 2006; Walks and Bourne 2006). Where attention has

been paid, it has typically been at a national scale, using cross-sectional data. For instance, Hurst

(2011) finds Canadian immigrants are significantly more indebted than non-immigrants, though

is unable to elucidate (given the national scale of the study) the causes and contours of this (that

is, whether such trends hold everywhere, or whether this is due to higher concentrations of

immigrants in highly indebted cities such as Vancouver). Collectively, over 225,000 immigrants

settle in Canada each year, with Toronto, Montreal, and Vancouver (TMV) attracting over 70

percent of these newcomers (Simone and Newbold 2014). In addition to being Canada’s premier

immigrant-reception metropolises, Toronto and Vancouver are the two most expensive real

estate markets in Canada (with Montreal less so on both counts, but nonetheless Canada’s one

French-speaking global city), and as such, analysis of household debt in TMV presents unique

opportunities for insight into the financial vulnerability of immigrants and visible minorities.

There are reasons for expecting that immigrants to Canada might be enticed into taking on more

debt than native-born Canadians, and because the vast majority of immigrants are also visible

minorities, it can be expected that higher rates of indebtedness amongst immigrants also translate

into higher rates of indebtedness among racialized communities. Higher rates of indebtedness

might be expected for two reasons. First of all, immigrants to Canada have typically lower

incomes than native-born Canadians, and their relative incomes have been declining over time

(Mok 2009; Walks 2011), and thus can be expected to have to rely on savings and debt to

supplement consumption. Immigrants to Canada, particularly racialized immigrants and those

with poor language skills, face discrimination in the job and housing markets (Murdie and Logan

2011). Additionally, research by Hurst (2011) and others (Faruqui 2008; Faruqui et al. 2012;

Meh et al. 2009) has found much higher levels of indebtedness (under a diversity of measures)

among those with low incomes.

6

Secondly, Canadian public policy has explicitly encouraged lenders to be more lenient in their

lending criteria with immigrants, particularly in relation to mortgage loans. Specialized mortgage

products for “newcomers” to Canada date back to before the early 2000s, and provide new

immigrants with more options to take on mortgages than have been provided to native-born

borrowers or longer-term residents. Much of this policy was implemented through the criteria

pertaining to mortgage insurance products offered by the Canadian Mortgage and Housing

Corporation (CMHC). In order to allow new immigrants, who rarely have any credit history in

Canada, to be able to purchase a house and access other loans on par with the non-immigrant

public, the federal government directed institutions such as the CMHC to offer specialized

mortgage insurance products. In turn, until the onset of the GFC, newcomers (with no minimum

period of residency required) could for many years take out a mortgage with a loan to value ratio

of 100 percent (meaning a mortgage is given without any down payment), while the maximum

loan to value ratio for long-term Canadian borrowers at the time was 95 percent (CMHC 2007,

2008). Similarly, the criteria regarding credit scoring were held to different standards. In 2008

newcomers requesting a loan to value ratio over 80 percent were merely “recommended” to have

a credit score over 600, while non-immigrant borrowers were “required” to have that base score

(see CMHC 2007, 2008 for guidelines). Perhaps most striking, newcomers were able to take

mortgages in the early 2000s without having any documented income or credit checks. While

these programs have been incrementally tightened since the GFC, and even after the federal

government brought in more restrictive lending criteria in 2012 (see Walks 2014), the private

mortgage insurers have continued offering specialized mortgage insurance products that allow

higher loan-to-value ratios and greater leverage to “newcomers”. Every major bank in Canada

(TD, CIBC, BMO, Scotiabank, and RBC) still offer newcomer packages in which they will give

‘special’ rates for mortgages, provide ‘preferred’ rates for car payments, and offer credit cards of

infinite varieties. This can be seen in Figure 1, where RBC’s newcomer package (as seen as an

advertisement on public transit) will provide immigrants with their first mortgage, car, and credit

cards. Such generosity may at face value appear to be beneficial to newcomers, and federal

policies are clearly intended to smoothly facilitate the integration of immigrants into Canadian

society. Yet the GFC and subprime/foreclosure crises in the US, which were clearly experienced

amongst lines of class, race, and immigrant status, call into question the ideology of

homeownership and housing as a means of asset-based welfare (Ronald 2008; Finlayson 2009;

Wainwright 2009; Immergluck 2009; Crouch 2009; Saegert et al. 2009). It remains to be seen

7

whether similar patterns apply in Canada, and how such policies might play out on the ground

and across space, despite the different system of mortgage finance found in Canada.

There is a clear need to understand how household debt is distributed across immigrant and

racialized communities in Canadian cities. Walks’ (2013a) study on household debt in Canada

found that while concentrations of immigrants and visible minorities were associated with lower

debt levels at the metropolitan scale, within the global (TMV) cities, it is the immigrant-

reception neighbourhoods – where multiple family households and visible minorities are most

concentrated – that have higher levels of debt, after controlling for other variables at both the

metropolitan and neighbourhood scales. Walks’ analysis did not examine the relationships

between household debt and immigration/minority status within individual metropolitan areas,

but instead combined them all into a single multi-level analysis. While this provides insight into

general patterns across all Canadian cities, it cannot indicate when patterns in one city deviate

from the others, nor can it identify which cities might deviate. This is a particularly important

issue, as Canada’s three “global” cities reveal very different immigrant settlement patterns from

other Canadian cities, and even from each other. It is in the global cities that the relationships

between racialization, immigration, and rising indebtedness are most important, as these are the

places rapidly concentrating immigrants to Canada. As Walks concludes (p.180): “This research

suggests relationships between immigration, race, and debt that vary dramatically among places

and racialized groups, and points to a need for more in-depth disaggregated research on this

issue”. This thesis aims to be a first step in developing such a research agenda, interrogating both

the specificities of place and of people in beginning to understand the complex relationships

surrounding household indebtedness.

8

Figure 1: Banks Profiting from Newcomers

Source: Photograph by author on city transit bus, 13 June 2014.

To evaluate the state of indebtedness, and spatial inequalities in the Canadian finance and

mortgage market sectors, I will examine levels and types of household debt in 2012 at the

neighbourhood (census tract) and metropolitan scales in Canada’s three largest metros – Toronto,

Montreal, and Vancouver (TMV). This thesis therefore seeks to answer the following questions:

(1) What is the spatial distribution of household debt, at the neighbourhood scale, within Canada’s global cities? Are concentrations of immigrants and visible minorities associated with higher levels and more predatory forms of household debt, after controlling for other factors and relationships?

(2) What role might housing markets, housing tenure, and neighbourhood composition play in the rising levels of household debt and of inequality & polarization? How might these variables relate to the levels of indebtedness found in immigrant and racialized neighbourhoods?

9

(3) How might the relationships between household indebtedness and immigrant/visible

minority status at the neighbourhood level vary between Canada’s global cities? Are the patterns similar, or do they differ significantly across metropolitan areas?

1.1 Chapter Outline

This thesis is structured as follows. Chapter 2 presents a literature review investigating the role

of debt in producing inequality as well as the GFC, and the systems of finance and financial

exploitation driving the economic collapse. Following this, the limited available international

literature on household debt is surveyed, after which the key theoretical frameworks

underpinning this thesis are presented. Chapter 3 provides discussion of the data and methods

used herein, while chapter 4 examines the descriptive and multivariate results, seeking to shed

light on the financial vulnerability of immigrants and visible minorities in Canadian society vis-

à-vis the accumulation of household debt. Chapter 5 concludes by way of integrating the results

through extension of the relevant literature, outlining how this thesis forms the basis for further

and more expansive critical analyses of household indebtedness, and through providing policy

recommendations that will begin to mitigate the impacts of the systemic inequalities in the

acquisition of debt within Canadian society.

10

2 Financialization, Household Debt, and Theories of Inequality: A Literature Review

2.1 Financialization, Innovation, and the GFC

The theory of risk-based pricing has become doctrine and ideology, used for well over a

decade to blame consumers for the consequences of an abusive industry, to justify a

deregulatory stance that encourages usury as ‘innovation’, and to sustain the mirage of

an ‘American Dream’ backed by high-risk, predatory credit.

(Wyly et al. 2009, p. 333)

The restructuring of both welfare states and financial markets has resulted in a ‘great

risk shift’, in which households are increasingly dependent on financial markets for their

long-term security: due to the financialization of home, housing risks are increasingly

financial market risks these days – and vice versa.

(Aalbers 2009, p. 285)

Financialization is a “profoundly spatial phenomenon”, and is subject to much debate in

literature surrounding its definition and the role it plays in capital accumulation (French et al.

2011; Pike and Pollard 2010; Walks 2013b). Financialization is defined as a mode of

accumulation in which profit making occurs increasingly through financial channels, as opposed

to trade and commodity production (Aalbers 2008, 2009; Arrighi 1994; Krippner 2005). The

financialization of mortgage markets requires homeowners and the houses acting as collateral be

seen as financially exploitable and capitalizable by the financiers, and is perhaps best

exemplified by the securitization of mortgages. Similarly, the politically driven practice of ‘risk-

based pricing’, has promoted victim blaming (of consumers), to justify financial innovation and

exploitation of both the middle class, but more often and especially, racialized and minority

communities (Aalbers 2008, 2009; Wyly et al. 2009). Risk-based pricing involves determining

the risk of default on behalf of the borrower, whereby the higher the risk a borrower presents, the

higher interest the creditor can charge (Soederberg 2012). There is a large body of evidence

contradicting the tenets of risk-based pricing, with empirical and legal studies being at the

forefront of debates (Engel and McCoy 2002, 2007; White 2004; Wyly et al. 2009).

11

Unfortunately, empirical work questioning the merit and validity of risk-based pricing often

requires industry data, and those demonstrating persisting racialized disparities in high-cost

credit using such data have followed by future restrictions in data access (Farris and Richardson

2004; Lax et al. 2004; Quercia et al. 2004; Warren 2002; Wyly et al. 2006).

The virtual collapse of the global financial system, beginning with subprime lending in the US, is

viewed by mainstream scholars and public writers (news outlets, etc.) as being the result of

unpredictable mistakes, market imperfections, and adverse ‘shocks’ to the macro-economy

(Demirguc-Kunt and Levine 2009). Such a perspective implies the view that the geography of

subprime and predatory exploitation is ‘flat’ (that is, not more prevalent or targeted at particular

neighbourhoods), and furthermore that there is nothing fundamentally wrong with the system

(Wyly et al. 2006, 2009). Though clearly debunked before, during, and after the GFC,

mainstream economists working in the academy, industry, and politics, still hold this view. The

subprime boom just overstretched, and lenders were forced to make loans to low-income and

minority groups through legislation such as the CRA (Aalbers 2009; Wyly et al. 2009). The

response on part of economists was for borrowers to accept their share of the responsibility for

borrowing recklessly, and to allow the market to adjust back to equilibrium, in addition to

supporting bailouts and capital injections worth over 29$ trillion (Economonitor 2011).

Risk-based pricing and the idea of loan securitization retain acceptance both amongst economists

and the public. Is it not only rational that lenders should be able to charge rates according to the

risk of consumer default? And should loans not be bundled into packages based on similar risks,

with investors rewarded based on the amount of risk they are willing to accept? Such logic

promotes popular acceptance: subprime lenders were too generous to overly enthusiastic and

risky borrowers (i.e., racialized and minority individuals and communities), and by attempting to

regulate this industry, it will only hurt those who need help the most (low-income and racialized

minorities). Instead, through deregulating financial markets the ‘American Dream’ can best be

achieved, whereas attempts to regulate the industry will dissuade lending to racialized

neighbourhoods (Wyly et al. 2009). Subprime lending – loans made to borrowers with poor

credit histories, and often containing dubious terms or rates – is one form of risk based pricing

(Ashton 2009), with those borrowers under 600 FICO scores (see below) typically being

classified as subprime. Because low-income borrowers are more vulnerable to manipulation, and

because the terms are not always, or even often, spelled out fully for borrowers, subprime

12

lending became a form of predatory finance seeking to extract greater amounts of profit off of

the more vulnerable among the population. Yet it is justified through mainstream neoclassical

economic reasoning.

Geographies of subprime and predatory lending in the US show cities, regions, and nation states

that are “anything but flat” (Aalbers 2008, 2009 p.36, 2012; Wyly et al. 2006, 2009, etc.).

Instead, through risk-based pricing, financiers are able to extract class-monopoly rents; often in

the very neighbourhoods and communities that have endured racial and economic discrimination

for over forty years, pointing to generations of racialized inequalities. Credit rationing was the

dominant mainstream explanation for the redlining and discrimination of the 1980s, with the

price mechanism of markets in equilibrium being provided as the solution to allocate credit

efficiently (Stiglitz and Weiss 1981; Vandell 1984; Berkovec et al. 1994). Leading to enhanced

screening techniques, credit reporting measures, and surveillance systems, the neoliberal

paradigm of finance has continued to embrace the exploitation of racialized and low-income

populations (Saunders and Allen 2002; Miller 2003; White 2002; Wyly et al. 2009).

The two private government sponsored enterprises in the US – the Federal National Mortgage

Association (Fannie Mae) and the Federal Home Loan Mortgage Corporation (Freddie Mac) –

and one public institution – the Government National Mortgage Association (Ginnie Mae) –

were instrumental in institutionalizing secondary mortgage markets, credit scoring and risk-

based pricing, and were thus key components of the GFC (Aalbers 2009, 2012). Mortgage

profiles sold on secondary markets – that is, packaged in mortgage portfolios and sold to

investors, as opposed to being a direct relation between the lender and borrower (primary

market) – were both bought and guaranteed by these three institutions. Fannie Mae, Freddie

Mac, and Ginnie Mae were the driving force behind creating a unified mortgage market in the

US, from the regionalized and thus segmented previous methods of lending/borrowing.

Mortgage profiles sold on the secondary market are classified by risk-profiles, as risk determines

the portfolio’s selling price (Aalbers 2009, 2012). Lenders assess both whether the borrower will

be able and willing to pay a mortgage, through calculating housing costs and financial

obligations in proportion to the borrower’s income (Aalbers 2005, 2009; Stuart 2003). This

credit-scoring is necessary for lenders to sell mortgage portfolios on the secondary market, while

also fuelling risk-based pricing: charging high interest rates on loan applicants that have low

scores, and low interest rates on loan applicants with high scores. While developed in the US,

13

credit-scoring has become a globally-implemented phenomenon, albeit with local variation in the

way it is implemented.

The primary mechanism for “democratizing” credit through credit-scoring is done through

‘FICO’ scores. FICO scores measure and define financial risk as the probability of default by the

debtor (Soederberg 2012). In addition to promoting the ideology of the ‘ideal consumer’, FICO

scores can enact market discipline on borrowers; typically those with scores below 600 are

classified as subprime, and are subject to stigma, degredation, and economic coercion (Leyshon

and Thrift 1999; Marrion 2007; Soederberg 2012). Furthermore, discourses of ‘consumer

protection’ promote the ‘hyper-individualized consumer’ (Harvey 2007), and are key in the

move away from collective rights of the welfare state to individual, market-based forms of

citizenship (Soederberg 2012). Practices of consumer protection thus enlist the market as the

enforcer of justice, punishing and excluding those with poor credit-scores and thus being too

risky to be lent to, through economic, social, and political exclusion (Soederberg 2012). Like

risk-based pricing, this is naturalized and accepted by the mainstream given it is based on

mathematical models, and therefore must be neutral and fair.

2.2 Household Debt in an International Context

Within advanced industrial economies, a number of general trends surrounding household

indebtedness emerge (Aniola and Golas 2012; Girouard, Kennedy, and Andre 2006; Brixiova,

Vartia, and Worgotter 2009; Beer and Schurz 2007; Brown and Graf 2013; Worthington 2006;

Turinetti and Zhuang 2011; Georgarakos, Lojschova, and Ward-Warmedinger 2010; Chawla

2011; Chawla and Uppal 2012; Hurst 2011; Barbara and Pivetti 2009). First, over the past thirty

years, in tandem with the rise of financial deregulation, household debt has significantly risen.

The rate of increase was the highest in the early 2000s, prior to the GFC. While high-income

households tend to have larger total magnitudes of debt (perhaps best explained by their ability

to take on large mortgages and car payments, etc.), it is the lower income households that are

usually subject to more predatory types of debt, making them more vulnerable. Typically, older

segments of the population (especially seniors) have the lowest levels of debt, while younger

cohorts, particularly those starting families, have the highest and most significant debt burdens.

Internationally, Aniola and Golas (2012) investigate the level and structure of household debt

across EU nations, highlighting significant variation. Debt as a percent of household disposable

14

income ranges from a low of 32.3 percent in Romania, to a high of 282.2 percent in Denmark.

The percent of this accountable to mortgages was highest in the Netherlands, at 92.1 percent, and

lowest in Romania (24.1 percent). Meanwhile, the share of total debt devoted to unsecured

consumer credit was highest in Romania, at 72.4 percent, and lowest in the Netherlands, at 4.2

percent, suggesting some interesting relationships surrounding the types of credit as it relates to

culture, the built environment (housing markets, etc.), and institutional histories. Finally, the

percent of households at least one month in arrears (in repaying at least one liability) was highest

in Bulgaria at 33.7 percent, (Romania was 26.6 percent), and lowest in the Netherlands (5.0

percent). Some trends surrounding the former Communist countries and their short institutional

histories comes into play here (Forrest and Yip 2012), and perhaps equally reflects why some

fared worse in the GFC than others (for the depth of penetration that the housing and mortgage

market had combined with the finance and banking sectors’ hold over the economy). Financial

distress in Australian households mirrors that seen in Canada, being higher in families with

children, and those of visible minorities (Worthington 2006). Similarly reflecting the Canadian

case, Beer and Shurz (2007) report that Austrian high-income households have a greater

magnitude of total debt than low-income households, though it is the latter that are more

burdened by debt, as it is the low-income households who have a higher relative debt obligation.

Logically following this is that lower income households are more vulnerable than their high-

income counterparts. This is echoed in OECD countries (Girouard et al. 2006), as well as South

Africa (Prinsloo 2002).

Critical literature on the geography of household debt is scarce. In addition to Walks’ (2013a/b)

original insights into the rise of household debt, Dodson and Sipe’s (2008, 2009) work on the

‘VAMPIRE index’ – the vulnerability assessment for mortgage, petrol and inflation risks and

expenditure – provide a complementary view. Aimed at understanding the spatial distribution of

petrol and mortgage vulnerability in Australian metropolitan areas, the VAMPIRE index

provides a framework for interrogating the long-term energy insecurity across the socio-

economic spectrum, highlighting the increased vulnerability of neighbourhoods in outer-suburbs,

which are both highly auto-dependent and mortgaged, to increased energy shocks, Dodson and

Sipe do not investigate the degree of household indebtedness, however merely ascertaining the

proportion of households with mortgages, and those that own multiple automobiles (Walks

2013b).

15

Montgomerie (2006, 2009) is one of the scholars producing credible work on, and theorizations

of, rising indebtedness. Through applying a neo-Gramscian approach, Montgomerie (2006)

examines the long-term impacts implemented by governments of the US, UK and Canada, to

achieve non-inflationary growth. Through studying historical structures, Montgomerie argues

that the rise in household debt was not as neoclassical economists purport – rational consumers

choosing to take on more debt due to the availability of credit and rising life standards – but

instead is one product of public policies implemented based on a Conservative political ideology

growth imperative. Through exposing the politically-driven nature of household debt’s growth,

Montgomerie shows that the social restructuring (such as socio-spatial distributions in income)

resulting from regulatory change in finance and labour markets is a main contributor to the

growth in household indebtedness. Montgomerie (2009) follows up this work by showing how

financial ‘innovation’ interacts with socio-economic transformations in US society to drive up

levels of unsecured debt amongst the middle class. She posits that financialization is key to

understanding increasing indebtedness given households’ perception of maintaining a certain

historically imagined standard of living (think of the post-war suburb idealized even today as the

‘American Dream’). Growing access to credit thus served to fulfill this dream, creating vast

disparities between those participating in the credit boom (left servicing this debt) to those that

did not. Finally, as noted by dos Santos (2009), Lapavitsas (2009) and Lysandrou (2011),

household indebtedness has arguably risen as a result of rising wealth for the rich (which

compels them to ‘invest’ some of their wealth in funds supplying credit to the new debt-based

innovations, in the absence of new productive uses for this capital), coupled with stagnant

middle-wage incomes, and the privatization of basic life goods (housing, health care, education,

etc.), which force wage earners to borrow to maintain any quality of life. Viewing household

debt as a social relation is key, and allows for the theorization that the major change in finance

and banking driving the GFC (and thus rising indebtedness) was banks turning to individual

wage income as a source of exploitable profit.

2.3 The Contemporary Canadian Debtscape

Until now, the discussion on finance, risk, predatory lending, risk-based pricing, and the GFC

have been framed in a largely US-centric view. This is warranted, given the central role played

by the US in the GFC and subsequent bailout, and the high degree of inequality and predatory

lending in that country. While Canada, and Canadian banks specifically, emerged from the crisis

16

relatively unscathed, it is not for reasons purported by mainstream economists and media outlets.

This is debunked by Walks (2014), who shows that banks did receive a substantial bailout in

Canada, but the bailout was conducted through government institutions and programs that were

authorized quickly through different Ministers, and thus did not receive the same level of media

or public scrutiny as received in the US. However (and perhaps unsurprisingly), Canadian banks

are exhibiting similar features and methods of economic exploitation as seen in the US pre-crisis

(albeit to an arguably lesser degree). Securitization was only further exacerbated by the crisis,

and finance and the mortgage market is more entrenched and more essential to the relative health

of the Canadian economy and society. Recent reports (Crawford et al. 2013; Bank of Canada

2013) are congratulatory to Canadian banks for their ‘resilience’, and embrace their international

recognition of prudence, stability, common sense and genius (Perkins and Erman 2009; Trichur

2009; Ratnovski and Huang 2009). And based on mortgage and housing market trends, one can

understand this surface-level view: Despite an initial plunge, Canadian housing prices have only

continued to sky-rocket, and housing prices are even more inflated than they were pre-crisis (see

Figure 2; The Globe and Mail 2014). Canadian institutions have attempted to reproduce the

economy largely as it existed before the GFC, with minor regulatory changes and so-called

‘tightening’ of supervisory roles (as well as some tightening of credit access). However, these

seem to have had little effect, as Canada’s real-estate market continues to be among the world’s

most over-valued, and Canadian households among some of most indebted (Walks 2013a/b).

Despite the ‘common sense’ claim that there are severe contradictions with trying to fix

indebtedness by encouraging households to take on more debt, housing is more ingrained to the

Canadian economy than pre-crisis (Aalbers 2008, 2009; Walks 2013a/b; Rosenberg 2010).

17

Figure 2: Housing Prices, Canada and the United States, 1999-2014

Source: The Globe and Mail, 23 April 2014.

In Canada, a number of studies have been conducted at the national scale on household debt,

primarily post-GFC when debt came to the forefront of public concern (Chawla 2011; Chawla

and Uppal 2012; Hurst 2011; Faruqui 2008; Faruqui et al. 2012; Meh et al. 2009). Given the

difficulty in obtaining pertinent data to household debt and privacy issues at smaller scales,

studies such Walks’ (2013a/b) on the geography of household debt in Canada are scarce. Despite

this, the national level studies re-iterate that which is seen in most advanced industrial nations.

Chawla and Uppal (2012) analyzing the one-off Canadian Financial Capability Survey in 2009

showed that young families, homeowners, the highly educated, and above average incomes were

associated with greater magnitudes of household debt. However, it is the relative levels of

indebtedness, as reflected in measures capturing the percent or rate of indebtedness of

households, that most accurately reflects the burden of debt on households (i.e., household A

with $100,000 income and $50,000 debt has a smaller relative burden than household B with

$20,000 income and $20,000 in debt). Similar to Switzerland (Brown and Graf 2013) and

Australia (2006), self-rated financial knowledge and knowledge of financial services/industries

was found to be associated with higher levels of debt, after controlling for socio-demographic

indicators. Hurst (2011) finds seniors are associated with lower levels of debt, while both those

aged 19 to 34 and those aged 35 to 49 being significantly more indebted than seniors – this

reinforces the theory of the life cycle, where young families purchase houses and take on debt,

18

later paying off debts through the life course. Life cycle theory does not cover the experiences of

lone parent households, which had significantly larger debt-to-asset ratios (over 80 percent), in

addition to being the largest group with high annual debt loads (measured as debt service ratios

of 40 percent or greater), as 9.6 percent of lone parent families had high annual debt loads,

compared to only 3.8 percent of couples with children, and 4.2 percent of the Canadian average.

Despite higher income households often holding larger magnitudes of debt, as Hurst (2011)

reports, financial insecurity as it relates to debt decreases with higher income. For example,

households with incomes under $50,000 had over 6 times the odds of having a high debt service

ratio, compared to those with income between $50,000 and $79,000. Most pertinent to this thesis

is that immigrants were found to be more highly indebted than Canadian born, with the latter

having a 60 percent lower odds of having a high total debt service ratio compared to immigrants.

In addition, the non-immigrant population had a debt-to-income ratio that was 43 percentage

points lower, while the odds of having a high debt-to-asset ratio was 38 percent lower than for

immigrants.

Canada’s mortgage market is arguably one of the most politically constructed and reconstructed

in the world. Mainstream economists and neoclassical scholars claim (Crawford et al. 2013) that

the US GSEs (Fannie Mae/Freddie Mac) operated for private profit, and only had an implicit

backing by the US government; but given this was only implicit, they faced little regulatory

supervision and therefore engaged in risky activities. This is contrasted to the role of the CMHC

in Canada, where it acts under an explicit backing from the Canadian government, and is

therefore subject to a rigid supervisory framework, promoting the CMHC to engage in prudent

business practices. Crawford and colleagues (2013, p. 58) claim that the CMHC “does not seek

to maximize profit through its activities, but rather to generate a return that is consistent with its

overall mandate”. The US GSEs, however, seek to maximize shareholders returns, as they are

private companies. Crawford et al. (2013) further claim that the regulatory framework in the US

forced lenders to provide loans to low-income households (while not citing specifically what

laws they mean, it is likely they follow the mainstream attack on the CRA, for which Aalbers

2009 debunks). What the laws actually do promote is equality of standards when lending to low-

income communities, that they not be treated differently based on their low-income, racialized,

or ethnic status (Aalbers 2009). Crawford and colleagues (2013, p. 60) attack the US subprime

mortgage market and lending scheme throughout their article, eventually turning attention to

19

Canadian households that are “…riskier than ‘prime’ borrowers. Although no standard

international definition exists, ‘non-prime’ or ‘non-conforming’ borrowers are generally

characterized as having weaker documentation of income, less capacity to make debt payments,

or an imperfect credit history. There is a continuum of risk for non-prime loans, ranging from

Alt-A and near-prime to the highest-risk subprime segment”. While this is largely semantic, they

fault by comparing the ‘non-prime, or non-conforming’ loans to those ‘subprime’ in the US, and

empirically demonstrate that Canada is ‘no where near’ the level to that of the US pre-crisis; for

instance, while the US subprime mortgage market peaked at 20% market share, the current

Canadian market share of ‘non prime’ or ‘non conforming’ mortgages is only 7%. What

Crawford et al. (2013) fail to realize is that while tighter regulatory standards and supervisory

practices over finance and mortgage markets in Canada should only to be applauded if the results

are socially progressive. Higher degrees of regulation on their own do not, a priori, mean there

are no distinctly predatory and exploitative social relations at play in the Canadian mortgage

market. Indeed, while this regulation may avoid a full-blown GFC (this is yet to be seen –

current housing market indicators would suggest no stoppage to the Canadian housing bubble;

see Figure 2) this does not mean that social relations, patterns and strategies, related to

profiteering from racialized/low-income discrimination are not at play. Indeed, the easy credit

available through the early 2000s to newcomers, and apparently “fixed” by stricter credit

regulation post-crisis, may merely be more efficient at both enticing people into debt while

keeping them making their payments.

Within the mortgage-market, risk-based pricing occurs differently Canada from that applied in

the US and elsewhere, and its main manifestations are less transparent in the Canadian case.

There are three subtle ways risk-based pricing appears within the Canadian context. First, among

those who are eligible for a “conforming” mortgage (that is, that meets the criteria for CMHC

mortgage insurance, according to the National Housing Act - NHA), credit scores and loan-to-

value ratios are used to determine what CMHC insurance premium borrowers have to pay (banks

add this premium to the total mortgage balance): those with less than 20 percent down payment

must pay this insurance (which protects the banks from default, not the borrower), while those

with down payments of 20 percent or more do not need any insurance. Second, the banks have

the ability to ‘sneak in’ risk-based pricing through, for instance, offering their ‘best’ clients extra

discounts on the posted rates. Since the Canada Mortgage Bonds (CMB) program was

20

implemented in 2001, the CMHC and private insurers have been insuring or buying up the NHA-

conforming mortgage-backed-securities (MBS) the banks send them, and thus the banks have

been willing to provide the majority of consumers their ‘special’ rates. Third, when and if

borrowers cannot access a loan through the traditional lenders, subprime ‘shadow’ lenders will

charge higher rates, and usually securitize these loans in private-label MBS. These private-label

lenders make up a small portion of total mortgages in Canada. In 2012 approximately $13.9

billion of mortgage credit remained outstanding in private-label MBS, or roughly 1.16 percent of

the $1,159 trillion in total outstanding mortgage credit in Canada (CMHC, 2013, Tables 21 and

23).

2.4 Theorizing Financialization, Debt, and Neighbourhoods: Class Monopoly Rent

There are a number of theoretical frameworks that aid in understanding relationships between

processes of financialization, debt accumulation, and capitalist profit extraction within the

settlement space of cities. Three frameworks are discussed at length here: Harvey’s (1974) class

monopoly rent, Soederberg’s (2010, 2012) debtfare state, and Walks’ (2010, 2013) ponzi

neoliberalism.

Gaining access to the exchange value of urban land is facilitated by monopoly control over land

protected by class position and force of law (Wyly et al. 2006). Harvey calls this relation class

monopoly rent: “Class monopoly rent arises because there exists a class of owners of ‘resource

units’ – the land and the relatively permanent improvements incorporated in it – who are willing

to release the units under their command only if they receive a positive return above some level”

(Harvey 1974, p. 253). Important here is both monopoly as in control of resources, as well as the

class positions of actors, and the conflicts that arise between clashing collective interests, fuelled

by systematic inequality in access to capital, political power, and land (Wyly et al. 2006).

Though complex, Harvey suggests we should not be confused by the system (small banks,

national banks, mortgage companies, etc.) as they all serve the same driving goal – to employ

national policy in localized contexts and to therefore create localized contexts in which class

monopoly rents can be realized (Harvey 1974). In sum, Harvey’s theorization of class monopoly

rent is primarily concerned with class, the force of law, and access to financial institutions that

21

permit the translation of use values to exchange values for purposes of capital accumulation

(Wyly et al. 2006, 2009).

Boasting geneaology to Adam Smith, this view of land rent disappears from scholarly literature

until Harvey (1974) reinvigorates debates surrounding rent with his seminal theory of class

monopoly rent (Wyly et al. 2009). Harvey began looking at classical theories of land rent in

order to understand contemporary urban problems; he emphasized the social relations

undergirding rent, as opposed to it merely be a simple transfer payment: “…actual payments are

made to real live people and not to pieces of land. Tenants are not easily convinced that the rent

collector merely represents a scarce factor of production” (Harvey 1974, p. 251). As suggested

by Wyly and colleagues (2009, p. 336):

“Each element of class-monopoly rent is crucial. Class matters because, in all capitalist

societies, the rights and privileges of ownership are central to power relations, political

conflict, and social inequality. Monopoly matters not primarily because, as Marx

suggests, the supply of land is limited, nor because landowners can become price-makers,

but rather because of the inherent monopoly associated with the legal status of ownership.

Owners enjoy a collective power in the marketplace by virtue of the fact that they are not

renters. Owners’ rights are codified in law and backed up by state protection and, if

necessary, armed police force; owners’ protection is by no means absolute or

unconditional, but it is much more than the security given to renters. Finally, rent is the

simple yet crucial economic measure enabling owners’ claims on the use of any

capitalizable asset with return subject to the ‘outcome of a conflict with a class of

consumers of that resource’ (Harvey 1974, p. 239)”.

Using Baltimore as his case study, Harvey divides the city into a series of housing submarkets in

order to analyze the class tensions within two spheres: speculator-developers vs. middle-class

suburban homebuyers, and low-income tenants vs. slum landlords. Noted by Anderson (2014),

while actors within the landowner class may act individually, they are compelled via competition

under capitalism to act in aggregate to maximize profit. Landlords are one moment in the process

of capital accumulation through class monopoly rents, and as profit percolates upwards through

the hierarchy, it is ultimately the financial industry that coordinates and realizes the value of

these rents.

22

Anderson (2014) notes that while Harvey’s seminal theory led to a rush of rent theorization in

Anglo-American scholarship, it has received less attention in the past two decades (Ball 1977;

Murray 1977, 1978; Amin 1977; Tribe 1977; Harvey 1982; Fine 1982; King 1987, 1989a). Until

being rejuvenated empirically by Wyly and colleages (see Wyly et al. 2006, 2009) the

methodological challenge of developing class monopoly rent beyond a heuristic device has been

prominent. While Smith’s rent-gap thesis (1979, 1996) generated significant scholarly attention,

the cultural turn of the 1990s has turned much mainstream academic attention away from

Marxist rent theory, and has instead focused on how the many complexities and local

contingencies (see Lees et al. 2008) in politics, economics, and culture influence cities broadly,

and gentrification in particular (Anderson 2014).

As Wyly et al. (2012, 256) note, while the institutional landscape since Harvey’s time has

changed, the “material relations of exploitation remain the same”. Debt payments, including

those related to mortgages used to access basic housing in inflated land markets, can be seen as a

form of class monopoly rent. As the state withdraws from providing social housing (as a

collective consumption good), resulting in a declining share of such housing (relatively in the

case of a growing city, absolutely in places where social housing is being sold off or converted to

private units, such as in the UK and the Netherlands), increasing proportions of middle and

lower-income households are forced to bid for housing on the private housing market,

compelling them to accept inflated values and to get into higher levels of debt. If segregation

concentrates over-indebted households in particular neighbourhoods, the spatial articulation of

(and negative effects of) indebtedness can be concentrated and confined to such neighbourhoods,

while sparing the neighbourhoods where the wealthy are concentrated. Thus, to the degree that

neighbourhoods segregate the wealthy from middle and lower-income households, the social

space of the city itself allows for neighbourhoods to become an instrument of class monopoly

rent. An analysis of debt flows in turn permits analysis of who is now imposing these rents, who

the rents are being extracted from, and what this says about the state of inequalities in urban

society at large.

2.5 Cannibalistic Capitalism and the Debtfare State

When the rents that lower and middle-income households are compelled to pay merely to access

basic housing (whether extracted as actual rent, or as debt payments on mortgages) impede the

23

ability of such households to access daily needs, not only might they be considered a form of

exploitation, but they may begin to impede the functioning of capitalism, and lead to crisis. This

is the basis of Soederberg’s theorization of the GFC. Soederberg (2010, 2012) produces a novel

analysis of the American credit card industry and credit card indebtedness, and derives two new

concepts to interpret and explain her findings – cannibalistic capitalism and the debtfare state.

Starting from the position that mainstream debates often take the social power of money, and the

coerceive and ideological roles of the neoliberal state for granted, Soederberg grounds her work

in a Marxian theory of money that views the social power of money through its ability to mask

and distort social relations around exploitation and domination in neoliberal capitalism. She

seeks to denaturalize credit card debt through critiquing the role played by money and the state in

creating and recreating everyday life.

Cannibalistic capitalism focuses on a form of accumulation that is fuelled by ‘secondary’ forms

of exploitation (those outside wage labour), as that is where workers’ real incomes are modified

(Soederberg 2010, 2012). Soederberg argues that the income streams derived from cannibalistic

capitalism rest upon a ‘gamble with the future’ (the ability and willingness of workers to make

the minimum interest payments on their debts), and posits that credit card issuers, and therein US

banks, need to actively recruit and retain the maximum amount of workers willing to indebt

themselves at the highest interest rates and in the greatest magnitudes in order to retain rising

levels of profits. These spaces of exploitation and dispossession require a constantly expanding

relative surplus population – that is, workers who are underemployed or fully unemployed.

Credit card companies aim at signing up the relative surplus population as they represent

revolving debtors – and therefore profit. However, credit cards represent a specific type of

money, capital, and profits, as they are classified as fictitious capital (capital not backed by

collateral) (Harvey 1999; Henderson 1998). Fictitious capital describes “…a situation whenever

credit is extended in advance, in anticipation of future labour as counter value” (Harvey 1999,

284). As Harvey (1999, p. 270 and p. 286) mentions, fictitious capital is both the ‘saviour of

accumulation’ and ‘the fountainhead of all manner of insane forms’ because credit ‘suspends

barriers to the realization of capital only by raising them to their most general form’.

Contemporary class monopoly rents act as a form of fictitious capital, as they provide profit

extraction in the future at expense of credit today (through, for example, mortgages and interest

rates).

24

Soederberg’s other important concept, the Debtfare State, “legitimizes, normalizes, depoliticizes

and mediates the tensions emerging from cannibalistic capitalism. Facilitating intensified and

expanded forms of predatory practices, the debtfare state protects banks through the ongoing

deregulation of finance and legal policies…within cannibalistic capitalism, the debtfare state has

enhanced the social power of money by legally and morally permitting credit card issuers

(banks) to generate enormous amounts of income from uncapped interest rates and by

continually extending plastic money to those in the relative surplus population [sic]” (Soederberg

2012, p. 495). The state imposes workers take on this debt in order to build credit histories, be

‘trustworthy’ and mold into the model consumer-citizen. The debtfare state uses coercive and

ideological measures under neoliberal capitalism to both encourage and enforce workers to take

on debt, often times to augment wage labour for social reproduction and basic life needs. Further,

the debtfare state has grown in power in tandem with the deregulation of finance since the 1980s,

since as Peck theorized in his workfare state (2001), the movement towards individualization,

maximizing work hours, and increasing competition has replaced state-backed social nets and

collective workers’ rights (Soederberg 2012).

2.6 Ponzi Neoliberalism

Highly related to the above discussion of Soederberg’s work is Walks’ (2010) concept of ‘ponzi

neoliberalism’. The latter represents both the form, and the outcomes, of the increasing tendency

for neoliberal public policies (including new forms of regulation) to be selectively implemented

in favour of the needs of finance capital, both to extract class monopoly rents from new

borrowers as well as to fund the restructuring of the global economy, including the offshoring of

productive activity. Walks’ concept of ponzi neoliberalism is geographic and multi-scalar, in that

it links the debt-based exploitation of lower-income households in the cities of the north to the

deindustrialization of these same cities. According to Walks (2010, 2013), the ascent of ponzi

neoliberalism can be roughly dated to the post-1997 Asian currency crisis, when new avenues for

capital accumulation narrowed, and the rate of profitability began to fall. As a result, interest

rates began to decline and predatory finance began to innovate with new debt-based instruments

and derivatives, and the ponzi tendencies already present within capitalism came to the forefront.

“An unsustainable, self-reinforcing system of imbalances and indebtedness then emerged, that

required constant increases in the growth of credit, the shift of productive capacity out of the

25

developed world, and the recycling of developing world export earnings into debt vehicles to

maintain consumption” (Walks 2010, 62).

Mirroring the arguments of Soederberg (2012), Walks argues that such a system requires

continuous restructuring of the welfare state, credit expansion and debt-fuelled consumerism

(finding ever-more numbers of households willing to indebt themselves), as well as requiring

significant bailouts of lenders and businesses to maintain not only profitability, but also the

appearance of economic ‘growth’ and perhaps most importantly the continued employment of

the working class (who instead of working in factories, now works at building condominium

housing). This highlights the contradictions inherent in ponzi neoliberalism, as it requires

extracting larger and larger amounts of input from the population who are facing job loss, serial

displacement, and increasing inequalities and polarization. It requires continuous buy-in to the

system that is controlled by, and mostly benefits, financial elites. It requires the continual

capitalization of everyday life, enforced by ever-increasing regulation by the (debtfare) state. For

its continuation, it also requires that those who are most victimized by the system internalize

their own failure, and for the victims (low-income and racialized groups) to take the blame when

the financiers take their ponzi dynamics too far – as witnessed most recently with the GFC

(blamed in the popular media on ‘reckless borrowers’, ‘uneducated buyers’, etc.). The ponzi

dynamics come to the forefront when it becomes transparent that the profits extracted from the

working class are not being used towards new technologies or production facilities, but instead to

pay off earlier capitalist speculators, and to provide bonuses to financial CEOs whose speculative

companies are bailed out on the public’s back. Not only has this system been re-ignited by state

interventions made in the name of Keynes, but it has emerged from the GFC as more integrated,

more essential, but also potentially more fragile, than before. There is a paradox inherent in the

expectation that those facing declining wages and job loss can be depended upon for ever-greater

consumption to prop up the economy.

The emerging urban debtscape is the concept that Walks (2013a) conceives in order to

understand the nexus between rising indebtedness across and between metropolitan areas, local

areas, socio-demographic groups and governments, as well as the set of policies, practices, and

cultural politics that both reproduce and react against it. The urban debtscape thus not only

encapsulates the quantitative socio-spatial outcomes of rising indebtedness across scales, but also

the qualitative effects that the use of credit in the city has on prevailing political ideologies,

26

citizen subjectivities, and policies surrounding property ownership and development across

multiple levels of government. Empirically, Walks (2013a/b) investigates mortgage (secured)

debt and aggregates unsecured debt (such as credit cards, student loans, vehicle loans, etc.). In all

Canadian metropolitan areas, mortgage debt makes up between one-half and three-quarters of

total household debt. Walks (2013) produces a geographic analysis for major metropolitan areas

to elucidate the patterns of indebtedness between old pre-war inner cities, post-war suburbs, and

suburban municipalities, which is helpful for, among other things, deriving the integration of

automobile travel and debt in the overall urban debtscape. Walks places geography at the

forefront, and through investigating scales ranging from the neighbourhood to nation state,

separates the effects operating at regional scales, from those at local scales of analysis. The urban

debtscape allows for an understanding and integration of the concepts of class monopoly rents,

ponzi neoliberalism, the debtfare state, and cannibalistic capitalism within the space of the city.

Analyses of this emerging urban debtscape can shed light on how different kinds of cities (those

facing deindustrialization, those fuelled by immigration, those with a booming natural resource

economy, etc.) produce new landscapes of indebtedness, and new social relations underpinning

class monopoly rent. It remains to be seen specifically through which mechanisms, spatial scales,

and to what degree class monopoly rents might be extracted through the mortgage and credit

card industries, as well as payday lenders and other predatory enterprises. Furthermore, it is

unknown how this effects different segments of the population (including whether immigrants

and racialized groups are more burdened than non-immigrants). How this contributes to, and

correlates with, income inequality and neighbourhood composition (quality and type of housing,

schools, green space, etc.) warrants further investigation.

27

3 Data and Methods

3.1 Data

This thesis examines how the levels and types of household debt map out spatially in relation to

concentrations of immigrants and racialized communities at the neighbourhood (census tract1)

scale, in the three largest Canadian metropolitan areas – Toronto, Montreal, and Vancouver

(TMV). In doing so, I interrogate the magnitude, relative burden, and composition of household

debt for immigrant and visible minority neighbourhoods. In doing so, I simultaneously

investigate the specific urban-geographical contexts of the three CMAs, to understand what role

neighbourhood composition, housing markets, and housing tenure play in the acquisition of

different types of household debt among neighbourhoods disproportionately concentrating

immigrants and visible minorities. Metropolitan areas in Canada act as good models for

understanding contemporary urban processes, Walks (2013) notes, because Canadian cities

reveal both similar and novel patterns of urban development, levels of inequality and socio-

spatial polarization, rates of growth/decline, to those seen in the UK, US, and Western Europe.

Meanwhile, neighbourhoods as the unit of analysis provide important insight into everyday life –

through the quality of housing, infrastructure, schools, health care, etc. – known as the

neighbourhood effects literature. This has been critiqued (Slater 2013), and should have dual

focus both on ‘where you live affects your life chances’ as well as the undergirding systemic

currents determining your life chances (such as processes of racialization, gentrification, and

capital accumulation).

The data used in this thesis come from two sources: the 2006 Canadian Census, and a proprietary

dataset created by consulting firm Environics Analytics, that captures levels of wealth, assets,

debts, and liabilities for households at the census tract (neighbourhood) scale, for all Census

Metropolitan Areas (CMAs) in Canada in 2012.

1 Census tracts are spatial units created by Statistics Canada as proxies for neighbourhoods and contain between

4,000 and 8,000 people on average. Their boundaries remain relatively stable over time, and follow identifiable features such as rivers, railway lines, and main streets. Census tracts are the most common unit used in Canadian neighbourhood research, not only because of their size, but because this is the level at which the largest range of quality census data are made available.

28

While Statistics Canada and the Bank of Canada produce national level statistics on household

debt, very rarely do they release data beyond the provincial scale. There are two surveys

pertaining to household debt, which are available at a micro-scale through Statistics Canada’s

Research Data Centers (RDC) – the Canadian Financial Capability Survey (CFCS, 2009), and

the Survey of Financial Security (SFS, 1999, 2005, 2012). It is the latter, SFS, that is the most

useful. Unfortunately, the most recent survey wave is not yet available from Statistics Canada,

and as such, the SFS must be analyzed in the future. The two private credit rating agencies in

Canada, Equifax and Transunion, collect some debt data, though are not rigorous or reliable

enough for academic research, as they lack institutional guidelines surrounding reliability and

quality checks, as well as only collecting data on newly issued credit (thus not capturing

outstanding debts). The Canadian Financial Monitor (CFM) is another potential source of debt

data, conducted annually by the survey firm Ipsos-Reid on 12,000 households, though this data is

unfortunately not publically released, does not systematically cover all neighbourhoods in

Canada, utilizes a non-random sample, is skewed towards wealthy individuals and households,

and perhaps most importantly does not correspond to the debt statistics provided by Statistics

Canada and the Bank of Canada at either the provincial or national scales.

The comprehensive, spatially aggregated Environics datasets were created as a result of the

above described data limitations. The Environics dataset was built both from the ground up and

from the top down, via an extensive process of “double-level optimization” involving iterative

proportional marginal calibration between the debt totals at two different spatial scales (see

Walks, 2013a, p.163 for details). The SFS, CFCS, the Survey of Household Spending (SHS)

provide the national/provincial-level debt surface and its relationships with social variables. At

the neighbourhood (census tract) level, five types of debt factored into the estimation of a first-

generation spatially comprehensive local debt surface: (1) data from the 2006 census at the

census tract level for mortgage and other housing costs as a proportion of income; (2) annual real

estate assessments for local properties from the provincial assessment agencies from 2006

onwards; (3) real estate sales and prices from the individual real estate boards in each

metropolitan region, at the scale of the local real estate zones, annually since 2006; (4) multiple

years of the panel survey data, with respondents geocoded within dissemination areas (spatial

units smaller than census tracts); and (5) data purchased directly from financial institutions

regarding the issuance of new secured and unsecured credit. This first-generation local debt

29

surface then underwent subsequent re-calibration by Environic Analytics through a series of

iterative constrained regression procedures so that the totals across neighbourhoods: (1) add up

to the provincial and national totals for mortgage, credit card, and consumer debt published by

the Bank of Canada and Statistics Canada; and (2) when examined at the national and provincial

levels, are fully consistent with the relationships between household debt and other social

variables documented in the SFS, SHS, and FCS and published by Statistics Canada (Hurst

2011). Thus, not only are the local totals consistent with the data available at the local level, but

when aggregated they reproduce the national picture reported by Statistics Canada. Reliability

statistics, derived from bootstrapping procedures, are provided for the data at the 0.05

significance level (p): among metropolitan areas (CMAs and CAs), the estimates of household

debt are accurate within ± 0.76%, while at the level of the census tracts, the estimates are

accurate within ± 5.33% (see Walks 2013, p.163).

The Environics data is therefore advantageous as it is highly reliable at small and large scales,

provides comprehensive coverage of urban Canada at the neighbourhood unit, and captures all

forms of debt. Unfortunately, as a commercial survey firm, their intricate methodology is

proprietary information, hindering the ability of scholars to replicate the results. Despite this, it is

the only valid dataset available to study household debt at a scale smaller than the province, and

thus is used by necessity. The primary dependent variable used in this thesis is household debt as

a percent of disposable (after tax) income. This variable was chosen as opposed to both debt as a

percentage of assets, and debt service payments as a percentage of income. The reasoning behind

this choice is that it provides the most comprehensive view of debt and the vulnerabilities

resulting therein (such as arrears, bankruptcy, foreclosure, etc.). This is contrasted with debt as a

proportion of assets, where there is no connection to income, and reveals only how exposed asset

values are to existing leverage, and the capacity to sell the assets if required. While debt service

payments as a percentage of income provides a solid view into the ability of households to carry

debt, this measure requires specialized data which is not available in the Environics dataset, and

thus is not analyzed here. In sum, of the three standard measures, it is household debt as a

percent of disposable income that is utilized throughout this thesis.

30

3.2 Methods

In order to examine the relationships between immigrant settlement and visible minorities

concentrations on the one hand, and levels of indebtedness on the other, the 2012 Environics

dataset was mapped to 2006 census tract boundaries. This allowed for incorporation of 2006

census variables in descriptive and regression analyses. The 2011 National Household Survey

was not utilized, as it is invalid, inaccurate, and unreliable. Hulchanski and colleagues (2013)

outline that the 2011 NHS should not be used because, among other things, it has fatal non-

response rates, has a high level of error, uncertainty in its level of socio-demographic

representativeness, fewer questions were answered on average compared to prior (mandatory)

censuses, no studies were conducted prior to the elimination of the long-form census pertaining

the accuracy or reliability of voluntary data collection.2 While somewhat reliable at the national

and provincial scales, the NHS purports large discrepancies at lower levels, largely resulting

from the high non-response rates. In short, despite the limitations of incorporating 2006 census

data with 2012 Environics data (being slightly older data for the independent variables), there is

no alternative.

Independent socio-demographic variables from the 2006 census–including those relating to

income, education, marital status, family structure, dwelling type and value, housing tenure, and

the key variables related to immigration status and visible minority status - were selected for

inclusion as independent variables, and compared against the household debt ratios derived from

the 2012 Environics dataset. A number of descriptive statistics and maps of debt ratios and

location quotients provide a window into the underlying distribution of indebtedness across

neighbourhoods of different kinds. To ascertain the levels of indebtedness among

neighbourhoods disproportionately housing immigrants and visible minorities, I took the mean

level of each visible minority group across all neighbourhoods in a city – acting as the ‘average’

concentration of that group in a neighbourhood – and ran cross-tabs for neighbourhoods which

2 Put most clearly: “The income data in the National Household Survey is not valid. It should not be used or cited. It

should be withdrawn. The 2016 census should be restored to the non-politicized, non-partisan scientific methodology that existed prior to the flawed 2011 National Household Survey” (Hulchanski et al. 2013).

31

had above average concentrations of each group3. Pearson correlations and partial pearson

correlations (controlling for rental tenure) for immigrant and visible minority neighbourhoods

and household debt types provide universal metrics of the strength of the relationships between

variables. The partial correlations work similarly, but also control for the relationship between

homeownership and overall debt levels (which is important, given the magnitude mortgages play

in the make up of household debt).

Multivariate inferential models were then estimated in order to determine whether any of the

patterns regarding the distribution of indebtedness across neighbourhoods derives from

immigrant or visible minority status, or from other variables. It could be, for instance, that higher

levels of household indebtedness in neighbourhoods dominanted by certain racialized groups is

due to low-income and poverty, and thus class rather than race or immigration status. The OLS

regression models estimated at the level of census tracts for each of the Toronto, Montreal and

Vancouver CMAs thus control for the effects of all the independent variables included in the

models, revealing whether immigration status or visible minority status have independent and

statistically significant effects. Four separate models were estimated for each CMA (thus, twelve

in total), with the dependent variables: household debt, mortgage debt, credit card debt, and other

consumer debt as a percent of disposable income, respectively. Stratifying these OLS models by

CMA allowed for comparison across TMV, to uncover what role specific urban contexts have in

the structuring and composition of household debt levels across neighbourhoods. The next

section of this thesis presents the findings of the descriptive and multivariate analyses,

concluding thereafter with a discussion and interpretation of these findings and their implications

for scholarship, public policy, and future research.

3 To provide an alternative but complementary view of the distribution of debt across immigrant and ethnic lines, I

also examined the distribution of each metric of household debt across quartiles for the three largest visible minorities (Chinese, South Asians, and Blacks) in addition to immigrants

32

4 Results: Household Debt, Immigrant Reception Neighbourhoods and Racialized Communities

This section seeks to uncover if neighbourhoods disproportionately concentrating immigrants

and visible minorities experience higher and more onerous debt burdens, and what the

composition of such debt burdens might be. For instance, are such neighbourhoods more likely

to have higher levels of secured (mortgage) debt, or unsecured debt (such as credit card and

consumer debts)? The latter types of debt typically come with high interest rates, permitting the

lender to extract greater rates of profit than other types of credit. While there is significant

variation between lenders and lending institutions, in Canada credit card and other unsecured

consumer debts can take on more predatory forms, not only through high interest rates, fees and

penalties, but also potentially through the targeting of loans by the more unscrupulous lenders at

low income, racialized, and vulnerable populations who have less choice in the credit markets

and less power to fight against predatory practices. At the same time, as noted in the

introduction, federal policies pertaining to conforming mortgages (eligible for mortgage

insurance) allow recent immigrants to Canada access to mortgage credit on easier terms than for

the native-born. Yet, it is not clear yet how this plays out on the ground, within the settlement

space of the city. It remains unknown whether neighbourhoods concentrating visible minority

and immigrant groups experience higher levels of either of these kinds of debts. Only once this

information is known can public policy can be enacted to try and mitigate unequal and unjust

burdens on certain segments of society, through, among other things, regulatory reforms of

financial activity and lending practices.

4.1 Descriptive Results

4.1.1 Metropolitan-level

Before the neighbourhood-level results are examined, it is important to understand the larger

context surrounding levels of indebtedness among households in Canada’s metropolitan areas,

and how these differ for the three largest cities. The level of household debt as a proportion of

income across all CMAs in Canada at the end of 2012 can be seen in Table 1. The Canadian

33

CMA weighted average4 for household debt as a percent of disposable income was 222.8

percent. Stated another way, if the total after-tax income of a household in that year was

$100,000, the total debt load for that household would be predicted to be about $222,800. Those

CMAs with total debt burdens above the Canadian average are almost exclusively located in

British Columbia, Alberta, and Ontario, while the lowest debt burdens are largely located in

Quebec, the Maritimes, and northern cities in Ontario. Looking at the three cities analyzed in this

thesis – Toronto, Montreal, and Vancouver (the “MTV” or “TMV” cities)– we can see that

Vancouver is the most highly indebted metropolitan area in all of Canada by a margin of almost

30 percent: the average household debt as a percent of disposable income is 310.6 percent.

Toronto reveals a level of household indebtedness that is above the Canadian average, at 242.6

percent, while Montreal’s levels is lower than both Vancouver and Toronto, at 198.8 percent.

The proportion of debt dedicated towards mortgages is approximately equal among the three

largest CMAs, at 75.0, 72.0, and 76.2 percent, for Toronto, Montreal and Vancouver,

respectively (see Table 2). Looking at the make-up of household debt raises questions about how

different types of debt are socially distributed. As we will see, the different kinds of debt –

mortgages, credit cards and other consumer debt – are not distributed equally among social

groups. From these tables, we can see that TMV have higher levels of debt than most Canadian

metropolitan areas, and in the case of Toronto and Vancouver, display higher total debt balances

per household. Secondary immigrant settlement areas, such as Kelowna, Saskatoon, and

Hamilton also have very high debt loads. However as it is the global cities that act as the major

immigrant reception areas in Canada, these highly indebted metropolitan areas raise questions

surrounding both the spatial distribution of debt, and how this relates at the neighbourhood level

to immigrant and racialized minorities. It is to these questions that I now turn.

4 CMAs weighted by the number of households, such that a CMA with higher numbers of households receives

proportionally more weight in determining the Canadian average.

34

Table 1. Total Household Debt as a Percent of Annual Income, By Urban Region, 2012

Urban Region (CMA/CA)

Household debt as a

percent of disposable

income

Household debt as a

percent of before-tax

income

Average total debt

balance per household

($)

Average household disposable

income ($)

Average before-tax household

income ($)

Total number

of households

(#)

933- Vancouver 310.6 211.0 180,791 58,214 85,698 944,161 932 - Abbotsford 284.8 199.0 152,691 53,616 76,911 61,987 915 - Kelowna 274.6 189.8 145,554 53,001 76,708 79,442 935 - Victoria 258.2 175.9 141,376 54,746 80,392 160,739 825 - Calgary 253.6 165.8 198,589 78,316 119,772 490,760 938 - Nanaimo 250.7 180.4 122,509 48,862 67,894 43,819 568 - Barrie 250.4 171.0 151,661 60,559 88,714 72,543 930 - Chilliwack 246.7 177.1 123,347 49,991 69,650 38,146 535 - Toronto 242.6 163.2 164,304 67,729 100,700 2,118,934 835 - Edmonton 235.2 156.2 155,773 66,234 99,722 474,899 925 - Kamloops 233.1 160.4 121,758 52,228 75,932 42,581 550 - Guelph 228.0 154.5 141,782 62,179 91,764 58,217 205 - Halifax 227.3 151.7 122,996 54,107 81,063 173,574 532 - Oshawa 227.1 153.3 143,587 63,220 93,646 137,590 CANADA AVERAGE 222.8 149.0 132,447 58,644 87,849 211,046 725 - Saskatoon 222.4 146.1 131,162 58,979 89,768 109,276 705 - Regina 218.1 144.1 131,618 60,334 91,328 89,151 537 - Hamilton 211.3 143.7 127,300 60,248 88,580 297,001 541 - Kitchener 209.2 142.3 127,237 60,820 89,432 192,579 001 - St. John's 206.8 133.1 126,142 61,012 94,789 82,100 830 - Red Deer 204.6 140.0 131,498 64,279 94,006 38,239 505 - Ottawa-Gatineau 199.6 131.4 129,009 64,632 98,158 529,188 320 - Fredericton 199.0 132.4 101,867 51,181 76,908 40,842 462 - Montreal 198.8 129.0 96,465 48,527 75,037 1,665,127 602 - Winnipeg 198.6 129.4 104,029 52,369 80,376 302,301 805 - Medicine Hat 198.4 138.8 114,632 57,777 82,572 31,197 970 - Prince George 195.3 137.7 106,600 54,569 77,442 35,532 810 - Lethbridge 194.7 133.4 101,261 52,014 75,889 43,696 529 - Peterborough 191.9 131.6 102,132 53,219 77,637 51,332 521 - Kingston 189.2 129.0 107,721 56,935 83,515 69,784 543 - Brantford 188.8 131.0 102,102 54,091 77,970 55,442 539 - St. Catharines-Niagara 184.4 127.5 94,990 51,521 74,495 167,067 305 - Moncton 182.8 122.4 89,795 49,135 73,387 60,997 459 - Saint Jean sur Richelieu 182.1 121.4 85,456 46,929 70,368 40,300 555 - London 178.1 122.1 98,828 55,478 80,911 205,381 559 - Windsor 175.5 121.3 91,547 52,156 75,447 131,414 575 - North Bay 172.0 119.4 90,697 52,721 75,936 28,617 421 - Quebec 169.0 109.4 80,834 47,843 73,863 359,158 310 - Saint John 168.7 112.8 86,042 50,995 76,254 53,693 522 - Belleville 167.9 118.7 86,438 51,496 72,842 40,072 433 - Sherbrooke 167.0 110.0 70,421 42,172 64,259 94,175 595 - Thunder Bay 164.9 113.0 84,850 51,467 75,358 54,027 450 - Granby 164.2 110.8 73,584 44,800 66,385 35,052 580 - Greater Sudbury 156.0 106.3 88,185 56,527 82,966 70,598 590 - Sault Ste. Marie 151.5 104.1 76,751 50,660 73,740 35,836 408 - Saguenay 150.7 97.9 66,151 43,900 67,553 71,307 562 - Sarnia 141.0 96.9 82,353 58,419 84,994 40,109 447 - Drummondville 136.7 92.4 55,930 40,922 60,552 40,045 442 - Trois-Rivieres 124.8 81.9 51,570 41,317 62,931 72,195 Source: Calculated by the author from custom data ordered from Environics Analytics.

35

Table 2. Composition of Household Debt, By Urban Region, 2012

Urban Region (CMA/CA)

Total household debt as a percent of

disposable income

Mortgage debt as a

percent of disposable

income

Credit card debt as

a percent of disposable

income

Other consumer debt as a percent of

disposable income

Mortgage debt as a

percent of total debt

933- Vancouver 310.6 236.5 13.8 60.2 76.2 932 - Abbotsford 284.8 203.9 15.0 66.0 71.6 915 - Kelowna 274.6 192.4 15.8 66.5 70.0 935 - Victoria 258.2 184.1 13.3 60.8 71.3 825 - Calgary 253.6 186.4 11.3 55.9 73.5 938 - Nanaimo 250.7 169.2 15.6 65.9 67.5 568 - Barrie 250.4 166.9 14.0 69.5 66.7 930 - Chilliwack 246.7 165.1 16.0 65.6 66.9 535 - Toronto 242.6 181.8 12.0 48.8 75.0 835 - Edmonton 235.2 159.2 13.2 62.8 67.7 925 - Kamloops 233.1 152.0 15.4 65.7 65.2 550 - Guelph 228.0 152.9 12.6 62.5 67.1 205 - Halifax 227.3 152.7 13.0 61.7 67.2 532 - Oshawa 227.1 161.9 11.6 53.6 71.3 CANADA AVERAGE 222.8 157.7 12.2 52.8 70.2

725 - Saskatoon 222.4 159.0 11.9 51.5 71.5 705 - Regina 218.1 157.4 11.1 49.7 72.1 537 - Hamilton 211.3 138.5 12.7 60.1 65.5 541 - Kitchener 209.2 139.1 12.5 57.6 66.5 001 - St. John's 206.8 156.6 11.9 38.2 75.8 830 - Red Deer 204.6 131.3 13.5 59.7 64.2 505 - Ottawa-Gatineau 199.6 135.8 12.2 51.6 68.0 320 - Fredericton 199.0 135.8 13.0 50.3 68.2 462 - Montreal 198.8 143.1 10.7 44.9 72.0 602 - Winnipeg 198.6 139.8 13.3 45.5 70.3 805 - Medicine Hat 198.4 112.9 14.9 70.6 56.9 970 - Prince George 195.3 114.2 15.1 66.1 58.4 810 - Lethbridge 194.7 105.9 15.6 73.1 54.4 529 - Peterborough 191.9 108.1 13.7 70.1 56.3 521 - Kingston 189.2 113.3 13.9 62.0 59.9 543 - Brantford 188.8 111.2 13.5 64.1 58.9 539 - St. Catharines-Niagara 184.4 102.4 12.9 69.0 55.6 305 - Moncton 182.8 122.1 12.8 47.9 66.8 459 - Saint Jean sur Richelieu 182.1 130.4 10.4 41.3 71.6 555 - London 178.1 107.9 12.8 57.4 60.6 559 - Windsor 175.5 99.4 13.6 62.4 56.7 575 - North Bay 172.0 97.8 14.8 59.5 56.8 421 - Quebec 169.0 120.1 9.6 39.3 71.1 310 - Saint John 168.7 107.9 12.8 48.0 64.0 522 - Belleville 167.9 83.8 14.8 69.2 49.9 433 - Sherbrooke 167.0 115.1 10.4 41.5 68.9 595 - Thunder Bay 164.9 91.9 14.0 60.0 55.1 450 - Granby 164.2 112.0 10.9 41.3 68.2 580 - Greater Sudbury 156.0 85.9 14.3 55.8 55.1 590 - Sault Ste. Marie 151.5 75.4 14.7 61.4 49.8 408 - Saguenay 150.7 99.6 9.0 42.1 66.1 562 - Sarnia 141.0 73.1 12.3 55.5 51.9 447 - Drummondville 136.7 88.8 9.6 38.2 65.0 442 - Trois-Rivieres 124.8 76.8 9.3 38.7 61.5 Source: Calculated by the author from custom data ordered from Environics Analytics.

4.1.2 Spatial Distribution of Household Debt at the Neighbourhood-level

In this section, we are seeking to understand the spatial distribution of debt at the neighbourhood

scale, within Toronto, Montreal and Vancouver. From this, we can begin to ascertain what role

neighbourhood composition and housing markets might play in the rising levels of household

36

debt. Specifically, where are debt levels the highest (in city cores, or suburban municipalities?).

Do immigrant reception neighbourhoods, and those with concentrated racialized minorities

display higher levels of debt? How might the relationships between household indebtedness and

immigrant/visible minority neighbourhoods vary between Canada’s global cities spatially? Are

there consistent patterns, or is there significant variation between these metropolitan areas?

Before we analyze the relationship between household debt levels and the distribution of

immigrants and visible minorities, it is important to get a handle on the general spatial patterns

evident in each CMA. It is notable that across each of the CMAs under study household debt as a

percent of disposable income is lowest in and surrounding the CBD, and higher in suburban

regions. This is partially to be expected given the dominant role mortgage debt plays in the

overall make up of household debt, coupled with typical lifecycle effects that see new families

moving into new housing in the suburbs, as well as seniors (who have usually paid off any

mortgages by the time they retire) moving into smaller but more accessible units in the inner

cities. These general findings also potentially point towards the role of decreased public transit

farther from the core of cities, and in turn the necessity of having one or more automobiles and

the need to finance these through debt (Walks, forthcoming in 2015). Figure 3 displays total

household debt for Toronto, and one can see that the amalgamated City of Toronto has

comparatively low debt levels, while it is in the outer suburban regions of Brampton, Vaughan,

and Markham, particularly their recent subdivisions, where debt levels are the highest. Debt as a

percent of disposable income in the City of Toronto is predominantly under 200 percent, while

suburban regions have levels of indebtedness as a proportion of disposable income that range on

average anywhere from 300 percent to a maximum of 541 percent (in the darkest shaded census

tracts). The spatial patterning of debt is made clear when debt levels are converted into location

quotients centered on the metropolitan average, with values under 1 (the census tracts shaded

white), showing below-CMA average concentrations, while value over 2.00, indicate more than

two times the concentration of debt as a proportion of income (Figure 4). Areas revealing lower

location quotients are generally concentrated within the City of Toronto, while higher location

quotients are more often found in the surrounding suburban municipalities, particularly

Brampton and Markham. It is notable that the latter are the municipalities in Toronto with the

highest proportions of recent immigrants.

37

Figure 3: Household debt as a percent of disposable income, Toronto, 2012

38

Figure 4: Location quotient for household debt as a percent of disposable income, Toronto, 2012

In Montreal, the lowest total debt values (as a proportion of household disposable income) are

found in neighbourhoods near the CBD, and in eastern Montreal (Figure 5). The highest levels of

debt extend outwards west in a ‘v’ shape, covering parts of Laval and the West Island

municipalities. These are the areas of Montreal that contain more Anglophones and Allophones

(speakers of languages other than French or English). This picture is reproduced in the patterning

of location quotients for levels of household debt (Figure 6). The municipality of Saint-Laurent –

an industrial suburb with a mixed population - has some of the most highly indebted

neighbourhoods, with minimum average debt levels of 300 percent. Similar levels of debt are

seen in neighbourhoods within the municipalities of Ste-Anne-de-Bellevue and Pierrefonds.

These trends are reproduced when looking at location quotients, as they have above-average debt

levels.

39

Figure 5: Household debt as a percent of disposable income, Montreal, 2012

Figure 6: Location quotient for household debt as a percent of disposable income, Montreal,

2012

40

Vancouver presents a particularly interesting example, and one that is somewhat distinct among

Canadian metropolitan areas, as virtually the entire CMA is highly indebted (Figure 7). While

the CBD of Vancouver has, similar to the other cities, some of its least indebted neighbourhoods,

relatively less-indebted areas are also found among neighbourhoods in some of the surrounding

municipalities. For instance, North Burnaby, Coquitlan, and South Delta all have relatively low

levels of debt (compared to the Vancouver average, albeit typically higher than the Canadian

average). However, there is a distinct pattern in Vancouver whereby it is in the cores of these

outer regions where debt levels are lowest (as a proportion of income), compared to the newer

housing areas on the periphery of these regions. Visualization of the location quotients for levels

of household indebtedness (Figure 8) reiterate this pattern, while highlighting one additional

interesting fact: the distribution of debt is more equal between neighbourhoods in Vancouver

than either Toronto or Montreal, by virtue of a smaller maximum location quotient (LQ = 1.63),

whereas Toronto and Montreal both have much higher maximum LQs – 2.23 and 1.98

respectively. This only shows, however, that the variation in levels of household indebtedness is

smaller in Vancouver, not that debt levels are less extreme, because the average level of

household debt is so much higher in Vancouver than elsewhere.

Figure 7: Household debt as a percent of disposable income, Vancouver, 2012

41

Figure 8: Location quotient for household debt as a percent of disposable income, Vancouver,

2012

4.1.3 Levels and Types of Household Debt in Immigrant and Visible Minority Neighbourhoods

In this section, neighbourhoods with above average concentrations of immigrants and visible

minorities are examined, to see whether higher proportions of these groups in neighbourhoods

are associated with higher (or lower) levels of mortgage, credit card, and other consumer debts.

Additionally, how these patterns vary between the three global cities is studied, to see whether

there is continuity or differentiation among metropolitan areas in regards to immigrant and

visible minority neighbourhoods. This further serves to inspect whether immigrant reception

neighbourhoods have any discernable patterning of debt types and levels (i.e., if immigrant

reception neighbourhoods have proportionally larger mortgage debt burdens, or credit card debt

burdens than the average neighbourhood within the metro, etc.).

The distribution of levels of household indebtedness across neighbourhoods is divided into

quartiles based on the proportion of the population deriving from the main visible minority

42

groups, as well as the proportion of the population who are foreign-born. The purpose of this is

to see whether and how debt levels change as the proportion of immigrant or visible minority

groups in a neighbourhood increase. In addition, levels and types of debt for those

neighbourhoods with above-CMA average concentrations of immigrants and visible minorities

are examined, to see whether these immigrant reception neighbourhoods have discernable

patterns of household indebtedness. Thereafter, correlations and partial correlations (controlling

for proportion of households that are renters in a census tract) were estimated to examine if

neighbourhoods disproportionately concentrating immigrants or visible minority groups had

stronger higher debt levels. This descriptive analysis helps elucidate patterns of indebtedness for

immigrant and visible minority neighbourhoods. However, the descriptive analyses are limited in

that they cannot control for other variables, as can be done in multivariate analysis. As such,

after presenting this analysis, we will move onto OLS regression models that control for a variety

of factors and relationships, and will show whether higher proportions of immigrants and visible

minorities in neighbourhoods are associated with higher and more predatory forms of household

debt.

In Toronto (see Table 3), neighbourhoods containing only three visible minority groups have

higher than average total household debt loads: Chinese, South Asian, and South-East Asians.

There is a 13 percent difference between average neighbourhood values for the debt-to-income

ratio in which there are higher concentrations of Chinese, compared to the CMA as a whole

(255.3 percent in neighbourhoods with more than 9.1 percent Chinese, compared to 242.6

percent for all other neighbourhoods). When the analysis is restricted to mortgage debt, however,

it is only neighbourhoods with above average proportions of Chinese that have higher levels of

as a percent of disposable income (187.2 percent compared to 181.8 percent CMA average),

suggesting that federal policies encouraging new immigrants to take on mortgages may have

mainly benefitted/affected this group in Toronto. Meanwhile, it is only neighbourhoods with

more Koreans that have lower levels of other consumer debts compared to the rest of the Toronto

CMA (47.0 percent vs. 48.8 percent). For neighbourhoods disproportionately concentrating all

other visible minority groups, the consistent trend is toward higher levels of indebtedness in

unsecured forms of debt.

43

Table 3. Toronto Descriptive Statistics

Descriptive Statistics, Toronto, 2012

Avg % concentration in CT (across entire

CMA)

# of CTs with > avg conc. Minimum (%) Maximum (%)

CMA NA 993 (total) NA NA Immigrant 43.16 512 8.34 78.22 Chinese 9.18 247 0.00 83.56 S Asian 11.90 337 0.00 77.27 Black 6.63 346 0.00 44.04 Filipino 3.20 360 0.00 29.60 Lat American 1.93 317 0.00 18.62 SE Asian 1.30 304 0.00 17.50 Arab 0.97 332 0.00 10.34 W Asian 1.39 282 0.00 16.98 Korean 1.03 282 0.00 14.00 Japanese 0.39 372 0.00 4.83 Types of Debt as % of Disposable Income, Toronto, 2012 Total HH Mortgage Credit Card Other CMA Avg 242.6 181.8 12.0 48.8 Immigrant 240.4 170.3 14.8 55.3 Chinese 255.3 187.2 13.8 54.2 S Asian 254.0 180.9 14.7 58.3 Black 235.4 163.6 15.0 56.8 Filipino 241.5 170.4 14.7 56.4 Lat American 224.8 156.4 14.8 53.5 SE Asian 251.4 181.3 14.6 55.5 Arab 241.3 174.0 13.8 53.4 W Asian 229.7 162.4 14.1 53.3 Korean 223.5 163.6 12.9 47.0 Japanese 223.3 162.2 12.3 48.8

Unlike Toronto, in the Montreal CMA (Table 4) all neighbourhoods hosting above average

proportions of each visible minority and immigrant group have lower total household debt levels.

This is mainly because of lower levels of mortgage debt in such neighbourhoods, since in many

cases the level of unsecured forms of debt (credit cards and other consumer debt) is higher.

However, in Montreal, neighbourhoods with above-average proportions of Latin American,

Korean, and Japanese all have, on average, lower levels of other consumer debts compared to the

CMA (44.0, 43.7, and 44.8 percent compared to 44.9 percent in the CMA). There is less

evidence that federal policies encouraging immigrants to access mortgage credit have a

noticeable effect at the neighbourhood level in Montreal.

44

Table 4. Montreal Descriptive Statistics

Descriptive Statistics, Montreal, 2012

Avg % concentration in CT (across entire

CMA)

# of CTs with > avg conc. Minimum (%) Maximum (%)

CMA NA 860 (total) NA NA Immigrant 20.93 384 0.71 72.34 Chinese 2.13 231 0.00 38.46 S Asian 1.89 217 0.00 42.81 Black 4.63 295 0.00 35.36 Filipino 0.59 157 0.00 31.31 Lat American 2.24 313 0.00 19.55 SE Asian 1.29 276 0.00 17.21 Arab 2.71 299 0.00 30.64 W Asian 0.40 232 0.00 7.34 Korean 0.13 165 0.00 5.04 Japanese 0.10 166 0.00 3.83

Types of Debt as % of Disposable Income, Montreal, 2012

Total HH Mortgage Credit Card Other CMA Avg 198.8 143.1 10.7 44.9 Immigrant 180.0 119.9 12.2 47.9 Chinese 178.4 117.2 12.1 49.1 S Asian 191.7 125.5 12.4 53.9 Black 175.4 114.4 12.4 48.6 Filipino 192.2 129.4 12.1 50.7 Lat American 164.0 107.9 12.2 44.0 SE Asian 178.9 120.8 11.9 46.3 Arab 179.4 119.6 12.1 47.7 W Asian 185.1 124.9 11.7 48.6 Korean 179.1 124.1 11.2 43.7 Japanese 188.4 132.2 11.4 44.8

Vancouver reproduces the main patterns seen in Toronto (Table 5), only with a greater number

of visible minority group-dominant neighbourhoods displaying higher total household debt loads

than the CMA average. In Vancouver, it is neighbourhoods disproportionately concentrating

Chinese, South Asians, Filipinos, and South East Asians that have higher than average total debt

loads, with South Asian-concentrated neighbourhoods representing the highest (333.1 percent

compared to 310.6 percent CMA average). Equally important, Vancouver is the only CMA of

the three where concentrated neighbourhoods of immigrants display higher than average total

debt loads (316.2 percent compared to 310.6 percent). Each of these neighbourhood groups, with

Filipinos being the exception, also have higher mortgage debt loads (as a proportion of average

household disposable income) than the CMA average, with South Asians again displaying the

largest magnitude difference (249.2 percent compared to 236.5 percent CMA average).

Vancouver is notably the most expensive housing market in the country. It would appear from

this evidence that the high housing costs in the CMA may compel many immigrant groups to

avail themselves of the looser access to mortgage credit facilitated by federal policies, such that

45

neighbourhoods where they settle reveal higher levels of debt. Given the lower levels of

household indebtedness in immigrant-reception neighbourhoods in Montreal – a metropolitan

area with less costly housing – coupled with moderate levels in Toronto (which lies between

Vancouver and Montreal in its housing costs), this evidence suggests it could be the interaction

between federal policies and housing market dynamics that leads to patterns of indebtedness

among neighbourhoods housing immigrant and visible minorities in Canada’s global cities.

Table 5. Vancouver Descriptive Statistics

Descriptive Statistics, Vancouver, 2012

Avg % concentration in CT (across entire

CMA)

# of CTs with > avg conc. Minimum (%) Maximum (%)

CMA NA 409 (total) NA NA Immigrant 38.30 199 8.47 78.35 Chinese 17.47 151 0.00 80.06 S Asian 9.50 100 0.00 76.61 Black 0.97 151 0.00 7.73 Filipino 3.62 155 0.00 19.03 Lat American 1.04 184 0.00 7.94 SE Asian 1.56 128 0.00 10.84 Arab 0.33 123 0.00 4.02 W Asian 1.28 104 0.00 17.87 Korean 2.11 142 0.00 18.78 Japanese 1.15 145 0.00 7.59

Types of Debt as % of Disposable Income, Vancouver, 2012

Total HH Mortgage Credit Card Other CMA Avg 310.6 236.5 13.8 60.2 Immigrant 316.2 236.7 15.2 64.3 Chinese 327.4 247.0 14.6 65.8 S Asian 333.1 249.2 15.0 68.9 Black 291.9 213.8 15.9 62.2 Filipino 316.7 235.0 15.6 66.1 Lat American 297.4 220.4 15.6 61.4 SE Asian 324.0 241.2 15.6 67.1 Arab 301.7 222.2 15.5 63.9 W Asian 298.0 223.8 14.6 59.6 Korean 292.2 218.6 14.6 59.0 Japanese 305.9 230.6 14.3 61.0

Perhaps the most striking finding is that in each of Toronto, Montreal, and Vancouver,

neighbourhoods containing greater than the average of every single visible minority and

immigrant group had higher levels of credit card debt than the CMA average, and

neighbourhoods housing the vast majority of visible minority groups had higher levels of other

unsecured consumer debts than the CMA average. These unsecured forms of debt, with typically

46

higher and unstable interest rates, dubious marketing schemes, and varied profit extraction

methods are more prevalent in neighbourhoods that have above-average concentrations of each

visible minority group, as well as of immigrants. This trend is confirmed when looking at

quartiles (Tables 6-8), as a clear gradient is observed whereby credit card debt levels increase as

the group’s concentration increases (going from one quartile to the next). While the results for

other types of consumer debt are more mixed, in all but two cases the highest quartile has the

highest level of unsecured consumer debts (with the exceptions being Chinese neighbourhoods in

Toronto, and Black neighbourhoods in Vancouver).

Table 6. Quartiles, Toronto, 2012

Toronto Immigrant Debt - Quantiles hhdebt mortgage creditcard other Low quantile 236.6 175.5 10.53 50.58 Below median 232.58 171.43 12.34 48.75 Above median 251.59 185.38 13.95 52.15 High quantile 247.43 174.82 15.69 56.93

Toronto Chinese Debt - Quantiles hhdebt mortgage creditcard other Low quantile 246.38 176.55 12.95 56.88 Below median 227.25 165.25 12.72 49.23 Above median 239.31 175.88 13.26 50.17 High quantile 255.89 189.28 13.9 52.71

Toronto South Asian Debt - Quantiles hhdebt mortgage creditcard other Low quantile 220.56 161.26 11.13 48.17 Below median 231.42 169.27 13.03 49.12 Above median 246.17 179.05 13.54 53.58 High quantile 268.23 196.07 14.88 57.28

Toronto Black Debt Quantiles hhdebt mortgage creditcard other Low quantile 237.45 177.57 10.88 49 Below median 253.51 190.51 12.54 50.37 Above median 236.11 168.57 14.18 53.36 High quantile 241.14 170.42 15.09 55.63

47

Table 7. Quartiles, Montreal, 2012

Montreal Immigrant Debt Quantiles hhdebt mortgage creditcard other Low quantile 210.19 154.49 10.47 45.23 Below median 182.51 131.11 10.79 40.61 Above median 180.2 130.63 11.41 38.16 High quantile 181.8 113.7 12.65 55.44

Montreal Chinese Debt Quantiles hhdebt mortgage creditcard other Low quantile 202.57 146.69 10.99 44.89 Below median 193.41 140.24 10.67 42.5 Above median 179.39 125.37 11.48 42.54 High quantile 181.38 119.4 12.1 49.87

Montreal South Asian Debt Quantiles hhdebt mortgage creditcard other Low quantile 199.46 145.52 10.6 43.34 Below median 184.75 132.88 10.95 40.92 Above median 182.85 130.12 11.21 41.52 High quantile 191.89 125.5 12.41 53.98

Montreal Black Debt Quantiles hhdebt mortgage creditcard other Low quantile 205.3 151.4 10.14 43.76 Below median 197.65 143.57 10.92 43.16 Above median 176.42 123.43 11.56 41.42 High quantile 178.86 114.79 12.62 51.45

Table 8. Quartiles, Vancouver, 2012

Vancouver Immigrant Debt Quantiles hhdebt mortgage creditcard other Low quantile 302.72 227.14 14.05 61.53 Below median 292.64 220.77 14.21 57.65 Above median 293.47 220.29 15.44 57.74 High quantile 328.05 245.37 15.4 67.29

Vancouver Chinese Debt Quantiles hhdebt mortgage creditcard other Low quantile 303.1 226.38 14.41 62.32 Below median 283.93 212.03 14.85 57.04 Above median 307.27 233.75 14.92 58.61 High quantile 324.19 242.27 14.97 66.94

Vancouver South Asian Debt Quantiles hhdebt mortgage creditcard other Low quantile 270.65 201.25 14.64 54.76 Below median 302.75 229.51 14.63 58.62 Above median 313.89 235.52 14.91 63.45 High quantile 332.4 248.74 15.09 68.57

Vancouver Black Debt Quantiles hhdebt mortgage creditcard other Low quantile 316.12 244.54 12.72 58.86 Below median 309.74 231.51 14.48 63.75 Above median 310.87 234.6 15 61.27 High quantile 282.71 206.62 16.49 59.6

48

Another picture of the relationship between neighbourhoods proportions of immigrants and

visible minorities and levels of household indebtedness is provided by pearson correlations (both

the straight correlations and partial correlations that control for differences in housing tenure).

This correlations analysis provides for more mixed results and point towards the complexity of

experiences related to household debt levels and neighbourhoods housing immigrants and

racialized communities. It is the partial correlations that are most instructive, as it is only after

controlling for the proportion of households who are renters and owners that it makes sense to

compare mortgage debt levels and immigrant/visible minority status. The partial correlation

results show that the neighbourhood proportion of Blacks and South Asians reveal the strongest

positive (though still only moderate in strength) correlations with higher total debt loads in

Toronto (0.215, 0.318) and Montreal (0.236, 0.268), while it is neighbourhood proportions of

Chinese (0.354), Blacks (0.362), and South East Asians (0.290) that reveal the strongest positive

correlations in Vancouver. Similarly, moderately strong (positive) correlations exist for

proportion of immigrants in a neighbourhood and that neighbourhood’s debt to disposable

income ratio. In Toronto, the partial correlation coefficient for the immigrant proportion is the

least strong among the three (0.290), with Montreal moderately stronger (0.341) and Vancouver

with the strongest correlation (0.440) between proportion of immigrants in a neighbourhood and

the levels of household debt as a percent of disposable income.

Thus, immigrant reception neighbourhoods appear to suffer higher levels of indebtedness,

though the particular composition of debt varies between places. What is clear, however, is that

there are relationships between race, ethnicity, immigrant status, and debt levels that are multi-

faceted and warrant further investigation. These results, particularly that neighbourhoods with

above CMA average concentrations of each visible minority group have higher than average

credit card debts and more often than not other consumer debts, point to important social justice,

distributive, and equality issues. While this cannot show, on average, if individual persons of

visible minority status have higher than average debt burdens, what it does show is that as the

concentration of a visible minority group within a neighbourhood increases, so too does the

neighbourhood’s average credit card and other consumer debts. These results are further

expanded through OLS regression models in the next section, to examine if presence of visible

minority and immigrant groups in neighbourhoods are associated with higher levels of debts.

49

Table 9. Toronto Correlations

Pearson Correlations, Toronto, 2012 Total HH Mortgage Credit Card Other Immigrant 0.061 -0.001 0.535 0.159 Chinese 0.176 0.156 0.137 0.113 S Asian 0.216 0.169 0.334 0.193 Black -0.045 -0.188 0.441 0.189 Filipino 0.004 -0.041 0.324 0.117 Lat American -0.156 -0.196 0.362 0.035 SE Asian 0.051 0.012 0.319 0.111 Arab 0.001 -0.016 0.163 0.033 W Asian -0.028 -0.036 0.161 -0.012 Korean -0.085 -0.047 -0.027 -0.180 Japanese -0.150 -0.110 -0.143 -0.185

Partial Correlations, Toronto, 2012* Total HH Mortgage Credit Card Other Immigrant 0.290 0.227 0.493 0.207 Chinese 0.150 0.125 0.195 0.099 S Asian 0.308 0.259 0.364 0.201 Black 0.215 0.135 0.359 0.257 Filipino 0.171 0.124 0.273 0.154 Lat American 0.071 0.032 0.265 0.095 SE Asian 0.197 0.158 0.284 0.139 Arab 0.086 0.072 0.134 0.051 W Asian 0.115 0.117 0.097 0.018 Korean -0.025 0.030 -0.077 -0.166 Japanese -0.157 -0.107 -0.178 -0.180

*Partial correlations controlling for % renters in a neighbourhood

Table 10. Montreal Correlations

Pearson Correlations, Montreal, 2012 Total HH Mortgage Credit Card Other Immigrant -0.116 -0.270 0.384 0.313 Chinese -0.120 -0.179 0.177 0.083 S Asian 0.045 -0.113 0.243 0.414 Black -0.104 -0.251 0.370 0.303 Filipino 0.038 -0.049 0.230 0.222 Lat American -0.269 -0.377 0.307 0.131 SE Asian -0.053 -0.161 0.206 0.243 Arab -0.104 -0.190 0.279 0.150 W Asian -0.067 -0.114 0.061 0.087 Korean -0.132 -0.131 0.010 -0.065 Japanese 0.005 0.025 0.027 -0.055

Partial Correlations, Montreal, 2012* Total HH Mortgage Credit Card Other Immigrant 0.341 0.128 0.209 0.515 Chinese 0.075 0.001 0.072 0.161 S Asian 0.268 0.050 0.175 0.497 Black 0.236 0.031 0.241 0.451 Filipino 0.188 0.073 0.195 0.271 Lat American 0.135 -0.013 0.090 0.321 SE Asian 0.193 0.048 0.097 0.338 Arab 0.176 0.067 0.156 0.259 W Asian 0.051 -0.010 -0.010 0.134 Korean -0.025 -0.014 -0.079 -0.021 Japanese 0.151 0.200 -0.047 -0.017

50

Table 11. Vancouver Correlations

Pearson Correlations, Vancouver, 2012 Total HH Mortgage Credit Card Other Immigrant 0.197 0.162 0.225 0.167 Chinese 0.243 0.206 0.072 0.222 S Asian 0.210 0.184 0.081 0.162 Black -0.173 -0.209 0.383 0.008 Filipino 0.101 0.054 0.274 0.174 Lat American -0.138 -0.151 0.340 -0.069 SE Asian 0.163 0.125 0.197 0.175 Arab -0.067 -0.091 0.208 0.030 W Asian -0.088 -0.061 0.013 -0.145 Korean -0.015 -0.011 0.042 -0.035 Japanese -0.110 -0.077 -0.012 -0.174

Partial Correlations, Vancouver, 2012* Total HH Mortgage Credit Card Other Immigrant 0.440 0.384 0.106 0.300 Chinese 0.354 0.303 0.036 0.274 S Asian 0.198 0.166 0.152 0.140 Black 0.362 -0.035 0.261 0.154 Filipino 0.278 0.211 0.197 0.282 Lat American 0.146 0.118 0.145 0.115 SE Asian 0.290 0.236 0.157 0.243 Arab 0.053 0.019 0.129 0.114 W Asian -0.023 0.007 -0.062 -0.108 Korean -0.020 -0.014 0.051 -0.038 Japanese 0.026 0.062 -0.164 -0.096

*Partial correlations controlling for % renters in a neighbourhood

4.1.4 Multivariate Results: OLS Regression Models for Canada’s Global Cities

While descriptive statistics are helpful in providing contextual information surrounding the types

and levels of debt taken on by households, it is through multivariate methods that we get the

clearest picture of the distribution of debt within and between neighbourhoods. Through the use

of backwards OLS regressions, in which only those variables that are statistically significant are

kept in the model, we can see where, and how, immigrant and visible minority groups influence

levels and types of debt at the neighbourhood level. With models one can ascertain if higher

concentrations of immigrants and visible minorities in neighbourhoods are associated with

higher and more predatory forms of household debt, after controlling for other factors and

relationships. In addition, we can see what role neighbourhood composition plays in the rising

levels of household debt, and how these variables might relate to the levels of indebtedness

found in immigrant and racialized neighbourhoods (as outlined in the previous section on

descriptive analysis). Finally, we can examine how trends vary between metropolitan areas, to

51

see if the patterns of factors related to the make up of debt in one global city confirm or

contradict that seen in others.

Given the findings from the literature (chapter 2 of this thesis), we can expect to find a gradient

in debt levels at the neighbourhood scale for different income levels, whereby the highest income

groups experience the largest magnitudes of debt, while the reverse is true for relative levels of

debt: that lower-income households have higher proportions of debt relative to their income.

Similarly, homeowners would likely have higher levels of debt (due to mortgages), while the

presence of seniors in neighbourhoods would tend to be associated with lower levels of debt

given the typical life cycle course, whereby seniors would have finished paying the majority of

their debts by retirement age (i.e., mortgages, car loans, etc.). The impacts of immigrant and

visible minority groups on debt at the neighbourhood scale is less certain, given the dearth of

scholarship on such topics, but one may expect them to have less options to obtain credit

compared to the domestic population (due to newcomers’ lack of credit history), and thus they

may be forced to take on debt with more unmanageable terms and conditions. Alternatively, due

to public policies which encourage immigrants to take on larger mortgages than non-immigrants

(discussed in the introduction) we might expect immigrants and racialized neighbourhoods to

have higher levels of mortgage debts, given the CMHC promoted (and still promotes) high

amortization periods and contractual terms for newcomer mortgages.

When looking at the OLS regression models for Toronto (Table 12), the proportion of seniors in

a neighbourhood display the expected relationship to debt levels, as they have negative

coefficients for total household debt (-3.105), mortgage debt (-2.040), credit card debt (-0.136),

and other consumer debt (-0.701). We expect the proportion of seniors to be inversely related to

levels of household debt, given life cycle theory. Interestingly, the coefficient for credit card debt

is quite small, suggesting that there is not as large of an impact as there is for other forms of debt.

Similarly, the percent renters in a neighbourhood show the expected relationship, having

negative coefficients for total household debt (-1.871) and mortgage debt (-1.445), and

unsecured consumer debts (-0.461), but with no relationship to credit card debt (-0.027). The

neighbourhood proportions of household income in relation to debt is distributed regressively, as

those in lower income brackets ($10k to 19k) have positive coefficients for each type of debt:

total household (1.738), mortgage (0.999), credit card (0.097) and other consumer debts (0.574),

while those in the greater-than-$100k bracket have negative coefficients for each types of debt (-

52

2.735; -1.847; -0.159; -0.777). Given that the dependent variables relate to debts as a percentage

of disposable income, these coefficients are related to the relative debt burdens within

neighbourhoods, as opposed to merely the magnitude of debt obligations. As such, these results

are conforming of the trends found elsewhere in the literature (Hurst 2011; Meh et al. 2009;

Walks 2013a/b, 2014) stating that lower income households and neighbourhoods have higher

relative debt obligations.

Might federal policy lead to higher levels of mortgage indebtedness among immigrant-reception

neighbourhoods? Table 12 shows that neighbourhoods housing more immigrants reveal positive

coefficients for mortgage debt (0.585), meaning that for every one percent increase in the

population share of immigrants in a census tract, mortgage debt as a proportion of annual

disposable income increases by 0.585. The positive effect on mortgage debt is the main reason

there is also a similar positive effect related to total household debt (0.681). Unsecured forms of

debt, meanwhile, reveal statistically significant (but slightly weaker) relationships with

immigrant settlement concentrations. There is a positive coefficient for credit card debt (0.043),

but a negative coefficient for other forms of consumer debt (-0.088). Note that it is

understandable that these latter coefficients are smaller, given that unsecured debt makes up only

around one quarter of total debt. Since the CMHC and financial institutions have provided

incentives encouraging lending to newcomers, it follows that neighbourhoods would have higher

levels of mortgage and credit card debts as the proportion of immigrants increases. The negative

coefficient for other consumer debts, on the other hand, suggest that immigrants may be having

more difficulty in obtaining forms of credit that in Canada are less likely to be securitized, such

as automobile loans and lines of credit. This differs from credit card debt given the ubiquity of

credit cards, the significant amount of advertising devoted to them (refer back to Figure 1), and

the necessity of their use in everyday life (for instance, with online purchases).

Turning to the proportion of visible minorities in neighbourhoods, we see that as the percent

Chinese increases (as a proportion of the total neighbourhood population), so too do credit card

(0.013) and other consumer debts (0.144). However, the percent Chinese in a neighbourhood is

associated with lower mortgage debt (-0.156), perhaps pointing to cultural factors, and to the fact

that many Chinese newcomers are able to pay for their housing in upfront, without mortgages

(see Ley 2003). The neighbourhood proportions of West Asians and Koreans also reveal positive

coefficients (2.587 for total household debt, and 1.350 for mortgage debt, and 2.326 for total

53

household debt and 1.616 for mortgage debt, respectively). Overall, this evidence shows

relatively strong and positive relationships with concentrations of visible minority groups of

Asian descent. This is contrasted with the coefficients for neighbourhood concentrations of

Blacks and Latin Americans. Neighbourhoods disproportionately housing Black populations

have negative coefficients for total household debt (-0.544) and mortgage debt (-1.934), while

Latin Americans also reveal negative coefficients (-0.583 for total household debt, and -1.537 for

mortgage debt). This could suggest differential access to financial information, levels of financial

literacy, and cultural/ racial differences in areas such as employment, money and finances, debt,

and credit use.

54

Table 12. Neighbourhood-Level OLS Regressions, Toronto, 2012

Census Variables Total household debt Mortgage debt (only) Credit card debt (only)

Other consumer debt (only)

% Immigrants 0.681*** 0.585*** 0.043*** -0.088** % Visible minority Chinese -0.156* 0.013*** 0.144***

Black -0.544** -0.583*** -0.032*** Latin American -1.934*** -1.537*** -0.428** Arab 0.561** W Asian 2.587*** 2.326*** Korean 1.350* 1.616*** Japanese 3.581* % Household structure Multi-family 1.405*** 1.671*** Non-family 0.821*** 0.666*** % Seniors (aged 65+) -3.105*** -2.040*** -0.136*** -0.701***

% Household income < 10k 0.416** 10k to 19k 1.738*** 0.999*** 0.097*** 0.574*** 20k to 29k 0.481*** 50k to 59k -1.105** -0.727* 70k to 79k -0.083*** 80k to 89k -0.137*** -0.559*** 90k to 99k -0.115*** > 100k -2.735*** -1.847*** -0.159*** -0.777***

% Unaffordable owners 0.718*** 0.754*** -0.108* Dwelling value ($) by 10k 0.313*** 0.507*** -0.038*** -0.154*** % Rent -1.871*** -1.445*** -0.027*** -0.461*** % Unemployment rate -1.175* -1.258** % Dwelling build date Pre-1946 0.520*** 0.446*** 1946-1960 0.011*** -0.070***

1991-2000 0.624*** 0.719*** -0.015*** -0.074*** 2001-2006 1.075*** 1.270*** -0.020*** -0.097***

% Dwelling type Semi-detached 0.197** -0.173*** Row house -0.417*** -0.248*** -0.186*** Apt. duplex 0.021* Apt. > 5 storeys -0.994*** -0.932*** -0.011** -0.092*** Apt. < 5 storeys -0.580*** -0.398*** -0.037*** -0.179***

% Marital status Single/Never married -0.601** -0.034*** -0.284*** Divorced 0.116*** Widowed 0.397***

Average # children 18.438** 23.360*** % Education < High school 0.036*** 0.238*** College 1.418*** 1.293*** 0.561*** Masters 1.010** % Dwelling status Minor repairs req. -0.043*** Major repairs req. 0.232*

Constant 285.49*** 138.902*** 20.947*** 96.694*** R2 0.821 0.846 0.796 0.626 aUnits of analysis are census tracts. Coefficients are for those variables remaining in the models after backwards OLS regression (to eliminate the effects of multicollinearity, and to maximize fit). Dependent variables, listed on the column headers, are calculated as a percent of disposable income. Sig. ***p<0.01, **p<0.05, *p<0.10. Source: Calculated by the author from custom data ordered from Environics Analytics, and from the Census of Canada, 2006

55

In Montreal (Table 13), the proportion of seniors in neighbourhoods has negative coefficients for

total household debt (-1.032), mortgage debt (-0.941) and other consumer debts (-0.271), though

credit card debts are not statistically significant. Interestingly, these are all weaker coefficients

than seen in the Toronto model, perhaps pointing to cultural differences between the two global

cities. Like Toronto, the proportion of income earners within a neighbourhood in the over-$100k

bracket has negative coefficients for total debt levels (-2.235), mortgage debt (-1.929), credit

card debt (-0.133) and other consumer debts (-0.415), although the only effect for the lowest

income bracket is a positive one for credit card debt. As expected, the concentration of renters in

neighbourhoods reveals negative effects for each type of debt (-2.207 total household debt; -

2.206 mortgage debt; -0.011 credit card debt; -0.256 other consumer debts).

Neighbourhoods disproportionately containing immigrants have positive coefficients for total

household debt (1.303), credit card debt (0.018), and other consumer debts (0.571). However, as

in the descriptive results, mortgage debt does not show up as significant. Higher proportions of

Chinese in a neighbourhood are associated with negative coefficients for total household debt (-

1.050) and mortgage debt (-0.676), but positive coefficients for credit card debt (0.050) and other

consumer debts (0.254). Neighbourhoods containing Latin Americans have negative coefficients

for total household (-1.053), mortgage (-0.859), and credit card debts (-0.064), (again similar to

Toronto), while Japanese have remarkably high (positive) coefficients for total household

(14.937) and mortgage debts (14.981): a one percent increase of Japanese in a neighbourhood

corresponds to over 14 percent increase in both debt types as a proportion of disposable income –

by far, the largest of any visible minority in any of the three CMAs. This is likely a spurious

correlation – with under 1 percent Japanese in the city, it is likely that the location of Japanese

clusters spatially corresponds with higher-debt neighbourhoods, but it is not likely that the latter

is predominantly due to Japanese financial distinctiveness.

56

Table 13. Neighbourhood-Level OLS Regressions, Montreal, 2012

Factors related to household debt levels at the census-tract level (OLS Regressions)a Montreal, 2012

Census Variables Total household debt Mortgage debt (only) Credit card debt (only)

Other consumer debt (only)

% Immigrant 1.303***

0.018** 0.571*** % Visible minority

Chinese -1.050*** -0.676*** 0.050*** 0.254** S Asian

-0.369*

0.693***

Filipino

0.081*** Latin American -1.053** -0.859** -0.064** 0.670***

SE Asian

-1.060** -0.113*** Arab

-0.603***

Korean -5.958***

-0.247* -3.108*** Japanese 14.937*** 14.981*** -0.339*

% Household structure Multi-family 2.712** 2.779*** 0.169**

Non-family 1.303*** 1.025*** 0.040*** % Seniors (aged 65+) -1.032*** -0.941***

-0.271**

% Household income < 10k

0.236* 10k to 19k

0.450* 0.031*

> 100k -2.235*** -1.929*** -0.133*** -0.415*** % Unaffordable owners 0.527*** 0.539*** 0.038***

Dwelling value ($) by 10k 0.698*** 0.878***

-0.165*** % Rent -2.207*** -2.206*** -0.011* -0.256*** % Unemployment rate -0.873** -0.884*** 0.049**

% Dwelling build date Pre-1946 0.206***

0.072**

1946-1960

0.059** 1961-1970

0.029***

1991-2000 0.736*** 0.612*** 0.016*** 0.150*** 2001-2006 0.629*** 0.962***

% Dwelling type Semi-detached -0.535***

0.030*** -0.296***

Apt. duplex 0.629*** 0.769*** 0.017*** 0.120*** Apt. > 5 storeys -0.496***

-0.024***

Apt. < 5 storeys

0.481***

-0.087*** % Marital status

Single/Never married -0.756*** -0.535***

-0.477*** Divorced

-1.571*** -0.064**

Average # children 51.448*** 44.662*** 2.092*** 8.415*** % Education

< High school

-0.036*** College 0.862*** 0.495*

Bachelors 0.747*** 0.970*** Masters

0.835**

PhD

-1.293*** % Dwelling status

Minor repairs req.

0.285*** Constant 172.18*** 127.111*** 8.365*** 58.98*** R2 0.795 0.81 0.596 0.621 aUnits of analysis are census tracts. Coefficients are for those variables remaining in the models after backwards OLS regression (to eliminate the effects of multicollinearity, and to maximize fit). Dependent variables, listed on the column headers, are calculated as a percent of disposable income. Sig. ***p<0.01, **p<0.05, *p<0.10. Source: Calculated by the author from custom data ordered from Environics Analytics, and from the Census of Canada, 2006

57

Vancouver (Table 14) as was noted earlier, has more evenly distributed debt levels, due to its

universally higher housing costs. Here we see the least variation amongst the coefficients for

concentrations of different visible minorities, as well as fewer class-based relationships between

debt and income across the income spectrum – although like Toronto and Montreal,

neighbourhoods with higher proportions of over-100k income earners have strong negative

coefficients for total household debt (-2.761), mortgage debt (-1.501) and other consumer debt (-

0.401). Similarly, there are strong negative relationships for the proportion of seniors in

neighbourhoods in relation to total household debt (-4.047), and mortgage debt (-4.461). These

coefficients are the strongest across the three global cities, perhaps due to the fact that not only

does Vancouver have the most expensive real estate market but that it is a magnet for wealthy

retirees due to its favourable climate and high quality of life. Likewise, as expected the

neighbourhoods with more renters are associated with lower total household debts (-3.249) and

negative coefficients for mortgage debt (-2.682). However, as in Montreal, rental tenancy is also

associated negatively with neighbourhood levels of credit card debt (-0.561).

Among Canada’s three global cities, it is in Vancouver that immigrant-reception neighbourhoods

have the strongest relationship to total household debt (1.431) and mortgage debt (1.554). As

with the descriptive statistics, this evidence suggests that federal policies facilitating access to

mortgage credit among immigrants has the greatest articulation within the social space of the city

where the housing market is tightest. In Vancouver immigrants are perhaps compelled to push

this access as much as they can (or rather, the banks are willing to do so, as intermediaries

between borrowers and the mortgage products and insurance criteria regulated by federal policy)

or risk not being able to access standard housing. There is, on the other hand, much less variation

in the coefficients for household indebtedness amongst visible minority neighbourhoods in

Vancouver, with no significant coefficients for any visible minority group variable, for either

total household or mortgage debts. In Vancouver, the division of neighbourhoods based on

mortgage debt levels is thus not one driven by racialization, but by immigration status.

Saying this, neighbourhoods with concentrations of Chinese again appear with positive

coefficients for credit card (0.041) and other consumer debts (0.196), while credit card debts also

have significant relationships for South Asians (0.058) and Koreans (0.128). Neighbourhoods

concentrating Black populations meanwhile have a strong positive coefficient for other consumer

debts (1.412), but no other significant coefficients, which could suggest difficulty in obtaining

58

(due to discrimination and/or levels of financial literacy) mortgages, and credit cards. Thus,

while the neighbourhood distribution of mortgage debt appears to be conditioned mainly by

immigrant status instead of race (after controlling for socio-demographic and other variables),

the distribution of unsecured debt-to-income would appear to be racialized.

Table 14. Neighbourhood-Level OLS Regressions, Vancouver, 2012

Factors related to household debt levels at the census-tract level (OLS Regressions)a Vancouver, 2012

Census Variables Total household debt Mortgage debt (only) Credit card debt (only)

Other consumer debt (only)

% Immigrant 1.431*** 1.554*** 0.046** % Visible minority

Chinese

0.041*** 0.196*** S Asian

0.058***

Black

1.412** Korean

0.128***

% Household structure Multi-family

-0.210*** 0.433* Non-family 2.448*** 3.298***

% Seniors (aged 65+) -4.047*** -4.461*** -0.127*** % Household income

< 10k

-1.946*** 10k to 19k 2.008*** 1.294** 0.172*** 0.673***

20k to 29k

0.090** 40k to 49k

-0.456**

60k to 69k

0.149*** 70k to 79k

1.672* 0.126***

80k to 89k

1.706* 90k to 99k

0.114*

> 100k -2.761*** -1.501***

-0.401*** % Unaffordable owners 1.518*** 1.654***

Dwelling value ($) by 10k 1.187*** 1.269***

-0.187*** % Rent -3.249*** -2.682***

-0.561***

% Unemployment rate -3.337*** -2.335** % Dwelling build date

Pre-1946

-0.036*** -0.185*** 1946-1960

0.227***

1961-1970

-0.206** 1971-1980 0.462**

0.021*** 0.155***

1991-2000 0.620*** 0.432*** 2001-2006 1.276*** 1.368***

-0.195*** % Dwelling type

Semi-detached

-0.050* 0.342** Apt. duplex 1.160*** 0.576***

0.292***

Apt. > 5 storeys -0.905*** -0.819*** Apt. < 5 storeys -0.706*** -0.698*** 0.018***

% Marital status Single/Never married -1.059* -1.072** 0.074***

Divorced

0.228*** Average # children

-2.569***

% Education < High school

-0.379*** College 2.002**

Bachelors 1.169**

-0.148*** Masters

-0.160***

PhD 5.969** 7.042*** % Dwelling status

Minor repairs req. 1.603*** 1.779*** Major repairs req.

-0.096***

Constant 185.70*** 96.225*** 9.571*** 89.332***

59

R2 0.739 0.772 0.73 0.531 aUnits of analysis are census tracts. Coefficients are for those variables remaining in the models after backwards OLS regression (to eliminate the effects of multicollinearity, and to maximize fit). Dependent variables, listed on the column headers, are calculated as a percent of disposable income. Sig. ***p<0.01, **p<0.05, *p<0.10. Source: Calculated by the author from custom data ordered from Environics Analytics, and from the Census of Canada, 2006

In summary, in terms of both total household debt as well as credit card debt (only), immigrant

neighbourhoods are associated with higher levels of indebtedness, across each CMA. Put another

way, a one percent increase in the proportion of immigrants within a neighbourhood in Toronto,

Montreal, and Vancouver is associated with an increase in total household debt, and credit card

debt. In Toronto and Vancouver, immigrant neighbourhoods are also associated with higher

levels of mortgage debts (but not in Montreal). While there is much variation across the three

cities with regards to visible minorities and indebtedness, the one consistency is that the presence

of Chinese in neighbourhoods is associated with higher levels of both credit card debt, and other

consumer debt. The positive coefficients in each city represent that a one unit increase in Chinese

as a percent of the total population in a neighbourhood has a corresponding increase in credit

card and other consumer debt levels at the neighbourhood level. Thus, it appears that unsecured

debts are racialized, but open to local variation, while the effects of federal policy through

newcomer mortgage products appears to be affected by the tightness of the housing market in

each respective metro.

60

5 Discussion and Conclusion This thesis put forth three main research questions: first, how is household debt distributed

spatially at the neighbourhood scale within Canada’s global cities? Second, what role might

housing markets and neighbourhood composition play in the rising levels of household debt, and

how might these factors relate to the levels of indebtedness found in immigrant and racialized

neighbourhoods? Third, are concentrations of immigrants and visible minorities associated with

higher and more predatory forms of household debt after controlling for other factors and

relationships? How does this vary between Canada’s global cities? Are there any defining

patterns that re-appear in each city, or is there significant variation in the level and type of

neighbourhood indebtedness found across metropolitan areas?

This thesis began by investigating the spatial distribution of household debt within Canada’s

global cities. Within Toronto, Montreal, and Vancouver, the CBDs and city cores consistently

display lower levels of indebtedness, while it is in the suburbs and periphery regions where debt

levels are the highest. The distribution of debt levels across quartiles of neighbourhoods showed

that in each global city, credit card debts and other consumer debts increased as the

neighbourhood proportion of visible minorities and immigrants increased. The trend was slightly

different for mortgage debt and total household debt, as it was typically both the lowest quartile

and the highest quartile (having the neighbourhoods with the least and the highest concentrations

of immigrants and visible minorities, respectively) that had the highest debt levels.

Neighbourhoods concentrating visible minorities and immigrants have disproportionately higher

credit card debt levels, while also displaying higher levels of other consumer debts. These results

provide strong evidence that higher concentrations of immigrants and visible minorities in

neighbourhoods are associated with higher and more predatory forms of household debt.

Second, this thesis investigated the role housing markets, housing tenure, and neighbourhood

composition play in the rising levels of household debt and of inequality and polarization, while

examining which variables were the most significant in predicting levels of total household,

mortgage, credit card, and other consumer debts at the neighbourhood level, in each of the three

global cities. We can see that there are consistent patterns between the three cities in predictor

variables: neighbourhoods with higher proportions of seniors and renters have lower debt levels.

In Toronto, a one percent increase in the proportion of seniors within a neighbourhood is

61

associated with a -3.105 percentage point decrease it total household debt as a percent of

disposable income, while renters have a -1.871 percent decrease in total household debt

(Montreal’s coefficients are -1.032 for seniors, and -2.207 for renters, for total household debt

levels; Vancouver’s coefficients are -4.047 for seniors and -3.249 for renters for total household

debt levels). Debt burdens are regressively distributed across the income spectrum in all three

CMAs, albeit more in Toronto and Montreal and less so in Vancouver. Nonetheless, each CMA

revealed lower levels of debt in places with more rich households (incomes over $100k).

Third, once the above effects are controlled for, there is consistent evidence that neighbourhoods

with greater proportions of immigrants display higher total household debt levels in each of the

three global cities. However, patterns for each kind of debt - mortgage debt, credit card debt, and

other consumer debt levels – reveal mixed results and local distinctiveness. In Toronto, greater

proportions of immigrants exhibit higher levels of mortgage and credit card debts, but lower

levels of other consumer debts. In Montreal, neighbourhoods concentrating immigrants have

positive coefficients for both credit card debt, and other consumer debts, but there is not

statistically significant coefficient for mortgage debts. In Vancouver, there are positive

coefficients for both mortgage debt and credit card debt, but no significant coefficient for other

consumer debts.

Are racialized communities more indebted than other places? There is one clear trend:

neighbourhoods concentrating Chinese in each of the three global cities present higher levels of

credit card debt and other consumer debts. There are highly differential results when looking at

neighbourhoods with other visible minority populations. In Toronto, neighbourhoods with West

Asians (2.587) or Koreans (1.350) have higher total household debt levels, while

neighbourhoods with Blacks (-0.544) and Latin Americans (-1.934) have lower total household

debt levels. In Montreal, Chinese (-1.050), Latin American (-1.053), and Korean (-5.958)

neighbourhoods have lower total household debt levels, and while Japanese (14.937)

neighbourhoods have significantly higher total household debt levels, this is likely a spurious

correlation given the small proportion of Japanese living in Montreal (<1% total population), and

is likely resulting from Japanese living in highly indebted neighbourhoods. Meanwhile, in

Vancouver there are no significant coefficients for any visible minority for total household debt

levels (unsecured debts such as credit card and other consumer debts have significant

coefficients, and can be reviewed for each of the three cities in Tables 12-14).

62

These results point to an interaction effect between federal policy encouraging homeownership,

and housing cost. The findings presented here support an interpretation in which immigrants are

compelled to go into more debt in the most expensive metropolitan areas (particularly

Vancouver, followed by Toronto), to get into the housing market. This is exacerbated by

declining levels of social housing available, fewer affordable private rental units resulting from

the gentrification of the inner city, and a generally tighter housing market. Longitudinal studies

on the rate of homeownership amongst immigrants confirm these findings, and point to the fact

that the rise in homeownership rates does not necessarily act in tandem with that of housing

affordability, suitability, or quality (Simone and Newbold 2014; Mok 2009; Hiebert 2009).

However, given the many ailments of higher debt loads on households, families, and individuals,

it brings into question whether homeownership is the best choice of tenure, and whether it should

be pushed and advertised so strongly towards newcomers. Given the significant reduction in

funding for social housing on behalf of the Federal government, coupled with the fact that few

new rental units are being built compared to purchasable units, it appears they have little choice

in the matter – raising a serious issue of social justice. Equally, this research suggests there is a

large degree of variability in terms of vulnerability amongst visible minority neighbourhoods,

which keeps with the literature on immigrant and racialized communities and housing (Murdie

and Logan 2011). It remains to be seen whether this variability can be attributed to a

continuation of historic trends of discrimination in housing (Murdie and Logan 2011), or if the

acquisition of debt among racialized households and neighbourhoods represents a shift from old

inequalities of exclusion to new inequalities of over-inclusion (redlining to green/yellow-lining).

Federal government policies that encourage newcomers to get into the mortgage market

effectively encourage lenders to greenline new immigrants.

The results presented in this thesis fit with the theory of cannibalistic capitalism (Soderberg

2010, 2012), where the income streams derived from cannibalistic systems of capital

accumulation rests on banks and financiers actively recruiting and retaining the maximum

amount of people willing to indebt themselves at the highest rates and in the largest magnitudes,

for the capitalists to retain rising profits. Credit card and mortgage debt here are being turned

into fictitious capital (Montgomerie 2006), banking on future revenue streams backed by future

labour, and class monopoly rents based on debt payments. This is backed by what Soderberg

calls the debtfare state, which demands people take on credit to become trustworthy, develop

63

credit histories, and mold into model consumer-citizens under neoliberal capitalism. The state

uses ideological measures through marketing ploys to both encourage and enforce the vulnerable

taking on predatory forms of debt. Through doing this, the power of the state legal and political

system is backing the extension of the forms being taken by class monopoly rents, much like it

has with risk-based pricing and other financial innovations. By being based on mathematical

models (credit scores, etc.) the state can claim that the credit taken on by newcomers and visible

minorities is neutral, sustainable and fair, even as the latter groups become more indebted and

their debt payments key to understanding the business success of Canada’s finance and banking

system. This shows the degree of penetration of class monopoly rents in everyday life, as they

have become part of mainstream policy, ideology and discourse, accepted as the ‘usual run of

things’. In Canada, one way that the economy has remained buoyant is not only through the

labour of new immigrants, but the larger proportion of their incomes that they pay in the form of

debt payments to Canadian financial institutions.

As noted by Walks (2013b), financialization has aided in the creation of highly indebted

neighbourhoods, a new socio-spatial form with potential to aid in reproducing urban space and

inequalities, as well as the intensification and increasing polarization of class relations. Walks

showed that poorer neighbourhoods, on average, carried higher relative levels of debt,

particularly mortgage and credit card debts. Additionally, high housing costs and mortgage debt

levels have forced lower-income and racialized households to utilize unsecured forms of credit to

finance homeownership (again, given the disappearance of social housing in Canada, and the

lack of any new rental units), which permits those who entered the housing market earlier to

capitalize on significant profits. Ponzi dynamics appear here in the Canadian housing market, as

it requires a constant influx of new entrants to the market to take on increasing levels of debt to

obtain housing, the profits from which goes to the elite, who invest in debt products and various

securities (from which mortgages backed in MBS by the CMHC is one form). My research

confirms that it immigrant neighbourhoods are taking on disproportionately larger mortgages in

Toronto and Vancouver. These are the places concentrating the new entrants to the

homeownership market, as a result of the lack of other tenure choices, the ideological role played

by the State in pushing homeownership as the ‘Canadian Dream’, and current forms of socio-

spatial polarization in Canadian cities (one example is that many new immigrants settle now in

suburban regions of Toronto where there are scarce rental units, as they can no longer afford to

64

settle in the downtown, where historically new immigrants would have arrived and landed in

enclaves (Newbold and DeLuca 2007).

Class monopoly rents are also being extracted among racial lines, through both mortgage and

unsecured forms of debt, though the patterns vary between global cities, pointing towards the

importance of local political economic context. Mortgage debts are disproportionately felt

amongst both immigrant and racialized neighbourhoods, and class monopoly rents are able to be

obtained as many of these neighbourhoods are low income, thus requiring the homebuyers to

purchase mortgage loan insurance through the CMHC (for mortgages with loan-to-value ratios

higher than 80 percent), and in so doing fuelling the ponzi dynamics of the housing system.

Through requiring insurance, many low-income households will buy into the CMHC mortgage

insurance program, where the profits will be packed into securities and sold on the market to

investors. High-income households, meanwhile, can pay above the minimum 20 percent down

payment, thus avoiding the extra fees from mortgage insurance. In this sense, one can see debt

service payments towards the CMHC as fuelling a ponzi dynamic, transferring wealth from low-

income households and neighbourhoods to high-income ones.

This is creating new urban forms, as higher concentrations of immigrants and visible minorities

in neighbourhoods are associated with an increase in unsecured debt levels in each global city,

thus concentrating debt in those neighbourhoods. The neighbourhood unit is therefore important

as it presents both challenges and opportunities in the struggle over rising levels of household

debt: as debt increases in a neighbourhood, and the built environment, infrastructure, the quality

of parks and green space decline over time (and many new immigrants and racialized households

will settle in lower income neighbourhoods), new forms, questions, and issues of socio-spatial

justice arise (Slater 2013; Madden 2014). This suggests that if segregation concentrates highly

indebted households in particular neighbourhoods, the negative effects of indebtedness can be

concentrated and confined to these areas, while sparing those neighbourhoods where the wealthy

are concentrated. In short, to the degree that neighbourhoods segregate the wealthy from the

middle and lower-income households, the social space of the city itself allows for

neighbourhoods to aid in capital accumulation from debt flows, thus acting as class monopoly

rents. This implies that highly indebted neighbourhoods will contribute to the increasing

polarization of society, as it will segregate the low-income, high (relative) debt households from

65

the high-income, low (relative) debt households, and will continue to channel profits from the

former to the latter in forms of debt service payments and obligations.

Perhaps unsurprisingly, the now famous Mayor Ford of Toronto went on record (CBC 2013)

saying that the waterfront was no place for social housing to be either developed or obtained,

effectively arguing that these neighbourhoods should be reserved for the highest bidders. If that

is the case, where should new immigrants and visible minorities settle? The implication is that

they can live by industrial units, areas with little to no public transit, poor quality schools,

housing, food choices, and recreational facilities? This is contradictory to Canada’s reputation as

a country welcoming of immigrants, given the importance of housing in the socio-economic-

political integration of immigrants to Canada, as it is first housing immigrants seek upon arrival,

only after searching for language, educational, and employment opportunities (Teixeira and

Halliday 2010). Quality, affordable, housing is of the utmost importance to immigrant quality of

life, including their physical and mental health, social and community ties, distance to and

suitability of employment, and their overall satisfaction with the immigration process (Murdie

and Logan 2011; Newbold 2009, 2010; Simone and Newbold 2014). There are significant

opportunities for collective protest and resistance to these new forms of class-based

indebtedness, primarily through community organizations focusing on immigrant rights, anti-

gentrification movements, and the right to the city, and cross-pollination between these

movements, rallying around class lines, would aid in demanding social justice, financial and

institutional reform, and reclaiming the right to suitable housing. The influence of space and

place, race and immigrant statuses, housing quality and affordability, and federal financial and

institutional policy, are therefore key to the production of inequalities related to indebtedness,

and this should be examined further and at additional scales to provide supplementary insight.

There are a number of policy implications from this research, as increasing proportions of middle

and lower-income households have been forced to bid for housing on the private market, taking

on ever-higher levels of debt. This is especially true for immigrants in Toronto and Vancouver,

while less so in Montreal. Meanwhile, this points to uneven burdens on highly indebted

individuals and households, as well as on neighbourhoods disproportionately housing these

communities. This is supported by and encouraged through the state, federal regulation on both

mortgages and newcomer ‘packages’ offered by major financial institutions in Canada, and

further engulfs immigrants and racialized minorities into the Canadian housing market.

66

Meanwhile, to the degree that the Canadian economy is increasingly becoming one defined by

financialization and indebtedness, we can expect to continue to see a rise in the channeling of

class monopoly rents from low income, racialized neighbourhoods, to high income, non-minority

neighbourhoods. This is because as financial ‘innovation’ continues to gain momentum, new

forms, methods, and tactics to produce debt products will occur. The lower and middle classes

will use these debt products, while their payments will be channeled to the investor elites. This

can, in turn, concentrate debt in some neighbourhoods, while increasing wealth in others, thus

producing new forms of class-based inequalities.

Policy measures can be implemented to begin mitigating the impacts of increased indebtedness

of immigrants and visible minorities as well as Canadian society at large. While this thesis did

not study financial literacy, it is logical to assume that on average, newcomers to Canada may be

less familiar with the types of institutions, standards of practice, and terms/conditions of finance

in Canada, may have language barriers that prevent them from understanding contracts and

clauses therein, and as a result, can be more vulnerable to predatory rates, practices or terms. As

such, I would recommend financial literacy programs be provided for newcomers and made

available for ethnic minorities. While this thesis has not studied whether immigrants taking out

loans are less able to understand terms due to language differences, should future research find

that language comprehension issues fuels higher debt among immigrants, translators can also be

provided.

I would recommend an increase in financial regulation – to the benefit of the borrowers –

monitoring banks lending activity, mortgage terms, and conditions. While newcomer packages

are in place to ease immigrant transition into Canadian society, this thesis shows that these

packages can introduce predatory effects, especially in cases where other forms of housing

tenure may be more appropriate to a person’s income as opposed to homeownership. These

newcomer packages could be reformed such that immigrants have the same access to credit,

based on income and assets, that non-immigrants have (e.g. have the same loan-to-value ratios

for both newcomers and non-immigrants). Legal counsel on mortgage and loan negotiations

could help, such that borrowers could have someone raise questions on their behalf (and inform

them of any predatory clauses in the contract), though this is yet to be studied. If progressing

towards a more equitable and just society were a priority for the Federal government, more

suitable, affordable, and higher-quality housing options should be available to newcomers and

67

lower-income households, outside of the private land market – such as through increasing the

amount of social housing available. With current Canadian waitlists projected at over 150,000

households (close to 75,000 in Toronto alone), social housing has not received capital inputs for

decades (August 2014), and is in severe need of reversing trends of privatization, and

gentrification. This would help limit or reverse the take up of debt, as less credit would be

required for mortgages, less pressure would be placed on the credit system to get newcomers into

homeownership, and wage income could be better put towards life necessities and savings.

While this thesis has gone some way to shedding light on the relationships between the spatial

distributions of household debt, and of immigrants and visible minorities, there remain

limitations. One limitation of this thesis has been the fact that all immigrants are lumped together

in the same variable. As this label captures all immigrants, it masks the vast differences that exist

between family re-unification, economic/skilled/business immigrants, and refugees. In housing,

refugees consistently do worse across all measures – affordability, crowding, and suitability, to

name a few (Simone and Newbold 2014). Future work should try to find a work-around for this

variable, as there very likely are intricate and important processes at work, whereby business

class immigrants easily obtain more stable credit, but perhaps more difficulty obtained by

refugees. One method may be to collect primary data either qualitatively or quantitatively, to

ascertain the differences across immigrant admission classes with regards to types and levels of

indebtedness.

Given the finding of above average unsecured forms of debt for concentrated immigrant and

visible minority neighbourhoods in Toronto, Montreal, and Vancouver, some process relatable to

a ‘healthy immigrant effect’ might be at play5. In terms of access to credit, and predation on

behalf of banks and financiers, I question what role the duration of stay in Canada plays in the

determination of the level and mix of household debt among immigrant groups. It is not fully

clear how immigrants are targeted for credit, and whether they end up paying higher interest

rates or suffer under unmanageable terms, and/or if, over time, their access to more stable forms

of credit increases. This very likely intersects across lines of immigrant status

5 The healthy immigrant effect posits that immigrants’ health statuses are often better (more healthy) than the

domestic population prior to arrival and in the years directly post-arrival, but that their health statuses decrease to that of the domestic population over time.

68

(refugee/family/economic), visible minority status, racialization, and economic well-being, and

warrants further study. Future research looking at these relationships at the level of the individual

is needed to shed light on these issues.

The research contained in this thesis raises the need for a comprehensive investigation into the

financial and banking industries history in Canada surrounding predation on the poor,

marginalized, and vulnerable. The high levels of household debt and the additional payments

they generate from immigrants and racialized groups in Canada’s cities can be seen as a form of

Harvey’s class monopoly rent, extracted by those who own shares in Canada’s banks

(particularly as the latter bear virtually no risk by the issuing of mortgages, see Walks 2014).

Through a focus on debt, I seek to highlight how financialization is capitalizing upon racialized

differences in financial literacy. And with the development of the credit card industry since

Harvey’s theory was developed, and especially with financial ‘innovation’ over the past two

decades, capitalists and financiers are now tapping into the markets of future revenue streams

through providing highly predatory forms of credit to the poorest and most vulnerable segments

of the population. It is high time elites stop profiting on the poor, and the results presented in this

thesis, along with the corresponding policy recommendations, provide some initial evidence and

methods of action to collectively work towards socio-spatial justice in the unequal and polarized

state of Canadian society.

69

References

Aalbers, M.B. 2005. Place-based social exclusion: redlining in the Netherlands. Area 37(1): 100-109.

Aalbers, M.B. 2008. The financialization of home and the mortgage market crisis. Competition and Change. 12:2, 148-166

Aalbers, M.B. 2009. The sociology and geography of mortgage markets: Reflections on the financial crisis. International Journal of Urban and Regional Research 33, 281-90.

Allen, R. 2011. The Relationship between Residential Foreclosures, Race, Ethnicity, and Nativity Status. Journal of Planning Education and Research. 31:2, 125-142

Amin, S. 1977. Capitalism and ground rent. In: Imperialism and unequal development. New York, NY: Monthly Review Press.

Anderson, M.B. 2014. Class monopoly rent and the contemporary neoliberal city. Geography Compass 8(1): 13-24.

Aniola, P., Golas, Z. 2012. Differences in the level and structure of household indebtedness in the EU countries. Contemporary Economics 6(1): 46-59.

Arrighi, G. 1994 (2010). The long twentieth century: Money, power and the origins of our times. Verso Press.

Ashton, P. 2009. An appetite for yield: The anatomy of the subprime mortgage crisis. Environment and Planning A. 41:6, 1420-1441

Ball, M. 1977. Differential rent and the role of landed property. International Journal of Urban and Regional Research 1, pp. 380–403.

Barba, A. & Pivetti, M. 2009. Rising household debt: Its causes and macroeconomic implications – a long-period analysis. Cambridge Journal of Economics. 33:1, 113-1378

Beer, C., Schurz, M. 2007. Characteristics of household debt in Austria. Monetary Policy & The Economy 2(7): 58-78.

Berkovec, J.A., G.B. Canner, S.A. Gabriel and T.H. Hanman. 1994. Race, redlining, and mortgage loan performance. Journal of Real Estate Finance and Economics 9.3, 263–94.

Brixiova, Z., Vartia, L., Worgotter, A. 2009. Capital inflows, household debt and the boom-bust cycle in Estonia. William Davidson Institute Working Paper Number 965, 1-27.

Brown, M., Graf, R. 2013. Financial literacy, household investment and household debt: Evidence from Switzerland. Swiss Institute of Banking and Finance, Working Papers on Finance No. 13/1, 1-21.

70

Caskey, J.P. 1994. Fringe Banking: Check-Cashing Outlets, Pawnshops, and the Poor. New York: Russell Sage Foundation.

Caskey, J.P. 2005. Fringe banking and the rise of payday lending, in P. Bolton, and H. Rosenthal, (Editors), Credit Markets for the Poor. New York: Russell Sage, 11 – 45

CBC. 2013. No affordable housing on the waterfront, says Rob Ford. Accessed 15 July 2014. Available online: http://www.cbc.ca/news/canada/toronto/no-affordable-housing-on-the-waterfront-says-rob-ford-1.2287508

Chawla, R.K. 2011. The distribution of mortgage debt in Canada. Component of Statistics Canadda Catalogue no. 75-001-X.

Chawla, R.K., Uppal, S. 2012. Household debt in Canada. Component of Statistics Canada Catalogue no. 75-001-X.

Canadian Mortgage and Housing Corporation (CMHC). 2013. Canadian Housing Observer 2013.

Canadian Mortgage and Housing Corporation (CMHC). 2007. Standard purchase mortgage loan insurance factsheet.

Canadian Mortgage and Housing Corporation (CMHC). 2008. Newcomer mortgage loan insurance factsheet.

Conley, D. 1999. Being Black, Living in the Red: Race, Wealth, and Social Policy in America. Berkeley, C.A.: University of California Press.

Crawford, A., Meh, C., Zhou, J. 2013. The residential mortgage market in Canada: A primer. Bank of Canada, Financial System Review, December 2013: 53-63.

Crouch, C. 2009. Privatised Keynesianism: An unacknowledged policy regime. British Journal of Politics and International Relations, Vol. 11, 382–399.

Crump, J., Newman, K., Belsky, E.S., Ashton, P., Kaplan, D.H., Hammel, D.J., Wyly, E. 2008. Cities destroyed (again) for cash: Forum on the U.S. foreclosure crisis. Urban Geography 29: 745-84.

Darden, J.T., Wyly, E. 2010. Cartographic editorial-Mapping the racial/ethnic topography of subprime equality in urban America. Urban Geography 29: 745-84.

Debtdeflation 2014. Accessed online at: http://www.debtdeflation.com/blogs/manifesto/

Demirguc-Kunt, A. and Levine, R. 2009. Finance and inequality: Theory and evidence. Cambridge, MA: NBER Working Paper 15275. http://www.nber.org/papers/w15275

Ding, L., Quercia, R. G., Reid, C. K. and White, A. M. 2011. State antipredatory lending laws and neighborhood foreclosure rates. Journal of Urban Affairs 33: 451–467.

Dodson, J. and Sipe, N. 2008. Shocking the suburbs: Urban location, homeownership and oil

71

vulnerability in the Australian city. Housing Studies 23: 377–401.

Dodson, J. and Sipe, N. 2009. A suburban crisis? Housing, credit, energy and transport.Journal of Australian Political Economy 64: 199–210.

Dos Santos, P.L. 2009. At the heart of the matter: household debt in contemporary banking and the international crisis. Ekonomiaz 72(3): 55-77.

Dymski, G.A. 2010. Confronting the quadruple global crisis. Geoforum 41: 837-40.

Engel, K.C. and McCoy, P.A. 2011. The Subprime Virus: Reckless Credit, Regulatory Failure, and Next Steps. New York: Oxford University Press.

Epstein, G.A. (Editor) 2005. Financialization and the World Economy. Northampton, Mass.: Edward Elgar Publishing.

Fabozzi, F. (ed.) 2001. Handbook of mortgage-backed securities. Fifth edition, McGraw-Hill, New York.

Faruqui, U. 2008. Indebtedness and the Household Financial Health: An Examination of the Canadian Debt Service Ratio Distribution. Ottawa: Bank of Canada. Discussion Paper 2008-46.

Faruqui, U., Liu, X., Roberts, T. 2012. An improved framework for assessing the risks arising from elevated household debt. Bank of Canada, Financial System Review, June 2012, 51-57.

Fine, B. 1982. Theories of the capitalist economy. London, UK: Edward Arnold.

Finlayson, A. 2009. Financialisation, financial literacy, and asset-based welfare. British Journal of Politics and International Relations. 11:3, 400-421.

Forrest, R., Yip, N-M (eds.). 2011. Housing markets and the global financial crisis: The uneven impact on households. Cheltenham: Edward Elgar.

French, S., Leyshon, A., and Wainwright, T. 2011. Financializing space, spacing financialization. Progress in Human Geography. 35:6, 798-819

Galabuzi, G.E. 2006. Canada’s economic apartheid – the social exclusion of racialized groups in the new century. Toronto: Canadian Scholars’ Press Inc.

Gallmeyer, A. and Roberts, W.T. 2009. Payday lenders and economically distressed communities: A spatial analysis of financial predation. Social Science Journal. 46:3, 521 – 538

Georgarakos, D., Lojschova, A., Ward-Warmedinger, M. 2010. Mortgage indebtedness and household financial distress. European Central Bank Working Paper Series No 1156, 1-57.

Gerardi, K. S., and Willen, P. S. 2008. Subprime Mortgages, Foreclosures, and Urban Neighborhoods. Boston, MA: Public Policy Discussion Papers, Federal Reserve Bank of Boston.

Girouard, N., Kennedy, M. and André, C. 2006. Has the Rise in Debt Made Households More Vulnerable? OECD Economics Department Working Papers No. 535. doi:

72

10.1787/352035704305

Globe and Mail. 23 April 2014. Canada/US average home prices: Paper copy newspaper.

Gotham, K.F. 2009 Creating liquidity out of spatial fixity: The secondary circuit of capital and the subprime mortgage crisis. International Journal of Urban and Regional Research. 33:2, 355-371

Grover, M., Smith, L., and Todd, R., 2008, Targeting foreclosure interventions: An analysis of neighborhood characteristics associated with high foreclosure rates in two Minnesota counties. Journal of Economics and Business, Vol. 60, 91–109.

Graves, S.M. 2003. Landscapes of predation, landscapes of neglect: A location analysis of payday lenders and banks. Professional Geographer. 55: 3, 303-317

Harvey, D. 1974. Class monopoly rent, finance capital, and the urban revolution. Regional Studies 8:239–55.

Harvey, D. 1982. Limits to Capital. Chicago: University of Chicago Press

Harvey, D. 2005. A brief history of neoliberalism. Oxford University Press, Oxford.

Hernandez, J. 2009. Redlining Revisited: Mortgage Lending Patterns in Sacramento 1930–2004. International Journal of Urban and Regional Research. 33: 2, 291-313

Hiebert, D. 2009. Newcomers in the Canadian housing market: A longitudinal study, 2001-2005. The Canadian Geographer 53(3): 268-287.

Hulchanski, D., Murdie, R.A., Walks, A., Bourne, L. 2013. Canada’s voluntary census is worthless. Here’s why. The Globe and Mail, Accessed online at: http://www.theglobeandmail.com/globe-debate/canadas-voluntary-census-is-worthless-heres-why/article14674558/

Hurst, M. 2011. Debt and Family Type in Canada. Ottawa: Statistics Canada. Component of Cat. no. 11-008-X, April 21, 2011. Accessed online at: http://www.statcan.gc.ca/pub/11-008- x/2011001/article/11430-eng.pdf

Immergluck, D. 2009. Foreclosed: High-Risk Lending, Deregulation, and the Undermining of America’s Mortgage Market. Ithaca: Cornell University Press.

Immergluck, D. 2011. The local wreckage of global capital: The subprime crisis, federal policy, and high-foreclosure neighborhoods in the US. International Journal of Urban and Regional Research, Vol. 35, 130–146.

Immergluck, D. 2013. Too little, too late, and too timid: The Federal response to the foreclosure crisis at the five-year mark. Housing Policy Debate 23(1): 199-232.

Karger, H. 2005. Shortchanges: Life and Debt in the Fringe Economy. San Francisco: Berrett-Koehler Publishers.

73

King, R. 1987. Monopoly rent, residential differentiation and the second global crisis of capitalism: the case of Melbourne. Progress in Planning 28(3): 195-298.

King, R. 1989a. Capital switching and the role of ground rent: 1 theoretical problems. Environment and Planning A 21: 445–462.

King, R. 1989b. Capital switching and the role of ground rent: 2 switching between circuits and switching between submarkets. Environment and Planning A 21: 771–738.

Krippner, G., 2005, The financialization of the American economy. Socio-Economic Review, Vol. 3 (3), 173-208

Laderman, E. and Reid, C. K. 2008. Lending in low and moderate- income neighborhoods in California: The performance of CRA lending during the subprime Meltdown. San Francisco, CA: Community Development Working Paper Series, Federal Reserve Bank of San Francisco.

Lapavitsas, C., 2009, Financialized capitalism: Crisis and financial expropriation. Historical Materialism. 17, 114-148

Lees, L., Slater, T., and Wyly, E. 2007. Gentrification. London, UK: Routledge.

Leyshon, A., Thrift, N. 1999. Lists come alive: Electronic systems of knowledge and the rise of credit-scoring in retail banking. Economy and Society 28(3): 434+466.

Livingwagecanada 2014. Accessed online at: http://livingwagecanada.ca

Lysandrou, P. 2011. Global inequality, wealth concentration and the subprime crisis: A Marxian commodity theory analysis. Development and Change 42:183–208.

Madden, D.J. 2014. Neighbourhood as spatial project: Making the urban order on the downtown Brooklyn waterfront. International Journal of Urban and Regional Research 38(2): 471-97.

Manning, R. D., 2000, Credit Card Nation: The Consequences of America’s Addiction to Credit. New York, NY: Basic Books.

Marron, D. 2009. Consumer Credit in the United States: A Sociological Perspective from the 19th Century to the Present. New York, NY: Palgrave Macmillan

Meh, C.A., Terajima, Y., Chen, D.Z., and Carter, T. 2009. Household Debt, Assets, and Income in Canada: A Microdata Study. Ottawa: Bank of Canada, Discussion paper 2009-7

Miller, M.J. (ed.). 2003. Credit reporting systems and the international economy. MIT Press, Cambridge, MA.

Mok, D. 2009. Cohort effects, incomes, and homeownership status among four cohorts of Canadian immigrants. The Professional Geographer 61(4): 527-546.

Montgomerie, J. 2006. The financialization of the American credit card industry. Competition and Change. 10:3, 301-319

74

Montgomerie, J. 2009. The Pursuit of (Past) Happiness? Middle-class Indebtedness and American Financialisation. New Political Economy. 14:1, 1-24.

Murdie, R. A., and J. Logan. 2011. Precarious housing & hidden homelessness among refugees, asylum seekers, and immigrants: Bibliography and review of Canadian literature from 2005 to 2010. York University: CERIS Working Paper No. 84.

Murray, R. 1977. Value and theory of rent: part one. Capital and Class 3, 100–122.

Murray, R. 1978. Value and theory of rent: part two. Capital and Class 4, 11–33.

Newbold, K. B. 2009. The short-term health of Canada’s new immigrant arrivals: Evidence from the LSIC. Ethnicity and Health, 14(3): 1–22.

Newbold, K.B., Deluca, P. 2007. Short-term residential changes to Toronto’s immigrant communities: Evidence from LSIC wave 1. Urban Geography 27(7): 635-656.

Newbold, K. B. 2010. Linking immigrant settlement, health, housing, and homelessness in Canada. Canadian Issues/Themes Canadiens (Newcomer’s Experiences of Housing and Homelessness in Canada). Montreal: Association for Canadian Studies Fall 2010: 30-33.

Niedt, C., Martin, I.W. 2013. Who are the foreclosed? A statistical portrait of American in crisis. Housing Policy Debate 23(1): 159-176.

OECD. 2011. An overview of growing income inequalities in OECD countries: Main findings. Divided we stand, why inequality keeps rising, 21-45. Available online: http://www.oecd.org/els/soc/49499779.pdf

Perkins, T. and B. Erman. 2009. Why Canadian banks work. Globe and Mail 7 March, B1.

Pike, A. & Pollard, J. 2010. Economic geographies of financialization. Economic Geography. 86, 29-51

Prinsloo, J.W. 2002. Household debt, wealth and saving. SA Reserve Bank, Quarterly Bulletin, December 2002, 63-78.

Quercia, R. G., Stegman, M. A., and Davis, W. R. 2007. The impact of predatory loan terms on subprime foreclosures: The special case of prepayment penalties and balloon payments. Housing Policy Debate. 18:2, 311-46

Ratnovski, L. and R. Huang. 2009. Why are Canadian banks more resilient? International Monetary Fund Working Paper 152, IMF, Washington, DC.

Renuart, E. 2004. An overview of the predatory mortgage lending process. Housing Policy Debate. 15:3, 467-502

Ronald, R. 2008. The Ideology of Home Ownership. New York: Palgrave Macmillan.

Rosenberg, D. 2010. What’s behind Canada’s economic miracle? Housing. Globe and Mail 28 April [WWW document]. URL http://www.theglobeand mail.com/report-on-business/economy/

75

economy-lab/david-rosenberg/whats- behind-canadas-economic-miracle-housing/ article1549564/ (accessed 1 November 2010).

Ross, L. M, and Squires, G. D. 2011. The personal costs of subprime lending and the foreclosure crisis: a matter of trust, insecurity, and institutional deception. Social Science Quarterly, Vol. 92, 140–163.

Rugh, J.S. and Massey, D.S. 2010. Racial Segregation and the American Foreclosure Crisis. American Sociological Review. 75:5, 629-651

Saegert, S., Fields, D., and Libman, K. 2009. Deflating the dream: Radical risk and the neoliberalization of homeownership. Journal of Urban Affairs, Vol. 31, 297–317.

Sassen, S. 2009. When local housing becomes and electronic instrument: The global circulation of mortgages –A research note. International Journal of Urban and Regional Research. 33:2, 411-426

Saunders, A. and L. Allen. 2002. Credit risk measurement: new approaches to value at risk and other paradigms. Wiley, Hoboken, NJ.

Simone, D., Newbold, K.B. 2014. Housing trajectories across the urban hierarchy: Analysis of the longitudinal survey of immigrants to Canada, 2001-2005. Housing Studies, DOI: 10.1080/02673037.2014.933782

Slater, T. 2013. Your life chances affect where you live: A critique of the “cottage industry” of neighborhood effects research. International Journal of Urban and Regional Research 37: 367– 87.

Smith, N. 1979. Toward a theory of gentrification: a back to the city movement by capital, not people. Journal of the American Planning Association 45 (4), pp. 538–548.

Smith, N. 1996. The new urban frontier: Gentrification and the revanchist city. NY: Routledge.

Smith, T. E., Smith, M. M., and Wackes, J. 2008. Alternative financial service provid- ers and the spatial void hypothesis. Regional Science and Urban Economics, Vol. 38, 205–227.

Soederberg, S. 2010. Cannibalistic capitalism and the current crisis. Studies in Political Economy 86: 7-21.

Soederberg, S. 2012. The US debtfare state and the credit card industry, Antipode. doi: 10.1111/j.1467-8330.2012.01004.x.

Squires, G. D. 2004. editor, Why the Poor Pay More: How to Stop Predatory Lending. London, UK: Praeger.

Squires, G.D. 2009. Inequality and access to financial services, in J. Niemi, I. Ramsay, and W.C. Whitford (Editors), Consumer Credit, Debt, and Bankruptcy: Comparative and International Perspectives. Oxford: Hart Publishing, 11-31

76

Stiglitz, J.E. and A. Weiss. 1981. Credit rationing in markets with imperfect information. American Economic Review 71.3, 393–410.

Stuart, G. 2003. Discriminating Risk: The U.S. Mortgage Lending Industry in the Twentieth Century (Ithaca, NY: Cornell University Press).

Sullivan, T. A., Warren, E., and Westbrook, J. L. 2000. The Fragile Middle Class: Americans in Debt. New Haven, CT: Yale University Press.

Swift, R. (ed). 2013. The Great Revenue Robbery. Between The Lines: Toronto.

Taylor, J., Silver, J., and Berembaum, D. 2004. The targets of predatory and discrimina- tory lending: Who are they and where do they live? In G. D. Squires, editor, Why the Poor Pay More: How to Stop Predatory Lending. Westport, CT: Praeger, 25–38.

Teixeira, C., and B. Halliday. 2010. Introduction: Immigration, housing and homelessness. Canadian Issues/Themes Canadiens (Newcomer’s Experiences of Housing and Homelessness in Canada). Montreal: Association for Canadian Studies Fall 2010: 3-7.

Tribe, K. 1977. Economic property and the theorization of ground rent. Economy and Society 6, pp. 69–88.

Trichur, R. 2009. Banks to go on a shopping spree. Toronto Star 17 September, B1.

Turnetti, E., Zhuang, H. 2011. Exploring determinants of US household debt. Journal of Applied Business Research 27(6): 85-91.

Vandell, K.D. 1984. Imperfect information, uncertainty, and credit rationing: comment and extension. Quarterly Journal of Economics 99.4, 841–63.

Wainwright, T. 2009. Laying the foundation for a crisis: Mapping the historico-geograph- ical construction of residential mortgage backed securitization in the UK. International Journal of Urban and Regional Research, Vol. 33, 372–388.

Walks, A. 2010. Bailing out the wealthy: Responses to the financial crisis, ponzi neoliberalism, and the city. Human Geography. 3:3, 54-84.

Walks, A. 2011. Economic restructuring & trajectories of socio-spatial polarization in the Twenty-First Century Canadian City, in L.S. Bourne, T. Hutton, R.G. Shearmur, & J. Simmons (Editors), Canadian Urban Regions: Trajectories of Growth & Change. Oxford: Oxford University Press, 125-159

Walks, A. 2013a. Mapping the Urban Debtscape: The Geography of Household Debt in Canadian Cities. Urban Geography. 34 (2): 153-187

Walks, A. 2013b. From Financialization to Socio-Spatial Polarization of the City? Evidence from Canada. Economic Geography. 1-34. DOI: 10.1111/ecge.12024

Walks, A. 2014. Canada’s housing bubble story: Mortgage securitization, the state, and the

77

global financial crisis. International Journal of Urban and Regional Research. 1-30. DOI: 10.1111/j.1468- 2427.2012.01184.x

Walks, A., Bourne, L. 2006. Ghetto’s in Canada’s cities? Racial segregation, ethnic enclaves, and poverty concentration in Canadian urban areas. The Canadian Geographer, 50(3), 273-297.

White, L.J. 2002. The credit reporting industry: an industrial organization analysis. In R.M. Levitch, C. Majnoni and C. Reinhart (eds.), Ratings, ratings agencies and the global financial system, Kluwer, Boston.

White, A.M. 2004. Risk-based mortgage pricing: present and future research. Housing Policy Debate 15.3, 503–31.

Williams, R., Nesiba, R., and McConnell, E. D. 2005. The changing face of inequality in home mortgage lending. Social Problems, Vol. 52, 181–208.

Worthington, A.C. 2006. Debt as a source of financial stress in Australian households. International Journal of Consumer Studies 30(1): 2-15.

Wyly, E., & Holloway, S., 1999. ‘The colour of money’ revisited: Racial lending patterns in Atlanta’s neighborhoods. Housing Policy Debate. 10:3, 555-600

Wyly, E.K., Hammel, D.J. 2001. Gentrification, housing policy and the new context of urban redevelopment. Critical Perspectives on Urban Redevelopment 6: 211-276.

Wyly, E., Atia, M, Foxcroft, H. & Hammel, D. 2006. American home: Predatory mortgage capital and neighborhood spaces of race and class exploitation in the United States. Geografiska Annaler. 88 (B), 105-132

Wyly, E. K., Atia, M., and Lee, E. 2007. Race, gender, and statistical representation: Predatory mortgage lending and the US community reinvestment movement. Environment and Planning A, Vol. 39, 2133–2166.

Wyly, E., Moos, M., Kabahizi, E., & Hammel, D. 2009. Cartographies of race and class: Mapping the class-monopoly rents of American subprime mortgage capital. International Journal of Urban and Regional Research. 33:2, 343-364

Wyly, E., Ponder, C.S., Nettling, P., Ho, B., Fung, S.E., Liebowitz, Z., Hammel, D. 2012. New racial meanings of housing in America. American Quarterly 64(3): 571-604.