Economic and Social Reports
What’s included in Canadians’ rent?

Abstract

Rental costs often cannot be compared without accounting for differences across data sources, regions and dwellings (e.g., dwelling type, size and condition). Similarly, a failure to consider differences in terms of non-financial inclusions such as utilities, parking, appliances or air conditioning can undermine the validity of cost comparisons. Using the 2021 Canadian Housing Survey, this study explores the prevalence of such rental inclusions and their potential impact on rental costs. Results suggest wide-ranging variability by inclusion type, geography and dwelling characteristics. For respondents paying rent, common inclusions are water and other municipal services (71%); appliances (23% in Quebec, but 70% or more in other provinces); parking (53%); electricity (31%); and oil, gas and other fuels (26%). Rental inclusions are a valuable source of information to make rents comparable, such as in provincial cost comparisons. For example, the inclusion of air conditioning and appliances explains around 8% and 7%, respectively, of the difference in rental costs between Ontario and Quebec, while the inclusion of appliances accounts for around 11% of the difference in average rents between British Columbia and Quebec. Findings suggest future research on housing affordability and rental market pricing would benefit from factoring in rental inclusions to enhance the accuracy and validity of cost comparisons.

Author

Samuel MacIsaac is with the Social Analysis and Modelling Division, Analytical Studies and Modelling Branch, at Statistics Canada.

Introduction

One-third of Canadian households rent their primary residence. Debates weighing the benefits of renting versus buying remain hotly contested, mainly because of the complex nature of drawing meaningful value comparisons. But housing tenure is more than a financial or lifestyle decision. It is also a key correlate of numerous social, economic and health outcomes. Evidence suggests renters experience less favourable socioeconomic outcomes (Stick, Schellenberg and MacIsaac 2023), community belonging (Beaumont et al. 2021) and health outcomes (Mason et al. 2013; Clair et al. 2016), as well as lower reported life satisfaction (Zumbro 2014; Fonberg and Schellenberg 2019), on average, than owners. Also, there remains a lack of affordable housing among lower-income earners in Canada (CMHC 2023). Renters are more than three times as likely to be in core housing need^Note compared with homeowners, according to the 2021 Canadian Housing Survey (CHS).

Given the prominence of ongoing housing affordability debates and the elevated levels of precarity renters face, rental cost data warrant further attention. Problematically, rental cost data obtained from Statistics Canada and external sources often include a wide variety of amenities or services that complicate their comparability across dwellings. Survey^Note and census^Note estimates do not account for amenities or services included in rental costs that vary significantly across rented dwellings. Amenities or services included in rent are referred to as inclusions for the remainder of this study. Among respondents paying rent, common inclusions are utilities such as electricity (31%); oil, gas and other fuels (26%); and water and other municipal services (71%) (according to the 2021 CHS). Other inclusions include appliances (58%), parking (53%), air conditioning (18%), Internet (6%), cable (5%) and furniture (4%).

Rental inclusions are important considerations when comparing rental costs. Media, and housing debates more broadly, frequently refer to rental cost estimates from online listings (CBC 2022; Yun 2022), which tend to offer more timely information on the latest trends and better reflect market rates for prospective renters seeking to rent a new place. However, these commonly cited rental costs are rarely adjusted for qualitative housing differences, including rental inclusions. Even within government policy discussions, rental costs are infrequently studied beyond comparisons of apartment rentals by number of bedrooms across regions. More publicly available information is needed to better inform policy makers and housing affordability debates on comparable rental costs across dwellings that account for such inclusions. Failure to consider these costs is likely to lead to errors in measuring rents paid.

Given the dearth of information on rental inclusions, this study explores the prevalence of such inclusions and their potential impact on rental costs. The paper is divided into two main parts. First, it documents the prevalence of selected inclusions in rental costs across dwelling characteristics and geographies. Second, it presents tabular information and multivariate linear regressions that analyze the association between several rental inclusions and monthly rental costs using a hedonic pricing model. The findings underscore the importance of considering rental inclusions, among other factors, when analyzing rental costs.

Data

This study uses Statistics Canada’s 2021 CHS, which provides information on housing conditions and costs. Survey questions include topics such as monthly rent, utilities paid, rental inclusions (e.g., various utilities, appliances and air conditioning) and various housing characteristics (e.g., dwelling type, number of bedrooms and condition of the dwelling). Data were collected from January 4 to June 2, 2021, with Canada’s 10 provinces and the territorial capitals of Whitehorse, Yellowknife and Iqaluit as the target population.^Note

The 2021 CHS prioritized survey completion by the household member with the most knowledge of the household’s housing situation. Interviews were conducted using self-response electronic questionnaires and computer-assisted telephone interviewing, with an overall response rate of 47% that included a sample of 19,500 respondent households that rent their primary residential dwelling. Only respondents reporting having paid rent were included in the sample used in this study.^Note

The oversampling of households in social and affordable housing (SAH) ensures there are sufficient survey responses to produce accurate statistics for key housing variables across survey strata.^Note Household weights ensure the sample remains representative of the broader Canadian population.

Data on monthly rent paid may differ from other sources in two main ways. First, the 2021 CHS asks respondents to report the total monthly dollar amount paid for the dwelling rather than their individual portions of rent paid.^Note This distinction is important in the case of cohabiting renters, renters partially or fully supported by a parent or acquaintance, and other circumstances whereby the respondent did not pay the dwelling’s total rent. Second, in contrast with data on the rental market rates faced by prospective tenants (i.e., individuals seeking a new rental dwelling), this study provides an overview of all monthly rents paid by Canadians. As such, this study includes the rents of new and longstanding tenants, as well as the rents of tenants in the SAH segment. In terms of comparability, this difference suggests average rental costs reported in this study are likely lower than those of other sources studying market rates, because the rents paid by long-tenure and SAH tenants are typically lower than the rents advertised for recently listed properties.

For the purpose of studying rental inclusions and their impact on rental costs, the CHS contains variables that are unavailable in other surveys. While the 2021 Census of Population fields questions on the inclusion of utilities, they are framed as “included in rent or other payments,” making it impossible to discern whether they are included in reported rental costs. Except for parking and certain utilities, the Survey of Household Spending is similarly limited in the ability to distinguish between expenses that are included in or excluded from rental costs. In the case of the Canada Mortgage and Housing Corporation’s Rental Market Survey of rental property owners, managers and building superintendents, “no adjustments are made for the inclusion or exclusion of amenities and services such as heat, hydro, parking or hot water” (CMHC 2022).

Despite data from online rental website listings frequently containing rental inclusion details (e.g., in-building or in-suite laundry and gym access), they are seldom used as adjustments in publicly available rental cost analyses and reports. Moreover, while they inform on the latest market rates, listings data are rarely nationally representative, do not distinguish between listed prices and paid rent, and do not include SAH data. As previously stated, rental listings data also exclude rents paid by longstanding tenants whose rents are often substantially lower than recently listed rentals.

Given the limitations of alternative sources and the scarce information on rental inclusions, the CHS is well positioned to study the prevalence of rental inclusions and their impact on rental accommodation prices across Canada.

Prevalence of rental inclusions in Canada

The prevalence of rental inclusions varies by inclusion type. Table 1 shows that the most common rental cost inclusion in Canada is water and other municipal services, reported by 71% of households that rent their dwelling. Other utilities such as electricity (31%) and oil, gas and other fuels (26%) are less common. However, some inclusions, such as oil, gas and other fuels, may not be relevant for all dwellings—for example, those using electric heat. The inclusions of appliances (58%) or parking (53%) are quite common, reported by over half of renters. Air conditioning, though less common, is included in rent for one in five rented dwellings in Canada. Other inclusions, such as Internet (6%), cable (5%), furniture (4%) and other items (2%), are less common.

Rental inclusions vary by geography and dwelling type. While property owners may be more reluctant to provide utilities or other inclusions for certain types of dwellings, these features may be commonplace for other dwellings. Rental market expectations regarding specific inclusions may also vary across regions based on weather or other differences. For instance, air conditioning may be more desirable in some parts of the country than others. Similarly, the more pervasive tendency to rent in Quebec may differentiate its rental market dynamics from those of other provinces and territories.

Table 1 supports this view. It shows how the percentage of dwellings with rental inclusions varies by region and type of rental inclusion. One of the most striking cross-provincial differences observed is the lower rate of including appliances in tenants’ rent in Quebec. While other provinces include appliances for a minimum of 70% of rented dwellings, appliances are included in only 23% of dwellings rented in Quebec.

The inclusion of utility costs also varies across regions. Electricity is included in about 4 in 10 rented dwellings in Ontario and Manitoba; this is higher than in the territorial capitals (34%) and other provinces (29% or lower). Oil, gas and other fuel inclusions differ more substantially across regions. While least widespread in Quebec (12%), Newfoundland and Labrador (15%), and New Brunswick (18%), the inclusion of fuel-based utilities is most common in Prince Edward Island (55%), the territories (54%), Nova Scotia (41%) and Alberta (40%). As for water and other municipal services, inclusions in rent vary from 62% to 78% of rented dwellings.

Other types of inclusions similarly vary by location. The higher inclusion of parking in rents in certain regions largely aligns with the lower population density of that specific province or territory. Inclusions of parking are highest in Prince Edward Island (73%), the three territorial capitals (71%) and New Brunswick (69%). While air conditioning is least commonly included in the territorial capitals (6%), it is most frequently included in the rent of dwellings in Manitoba (41%), Saskatchewan (35%) and Ontario (27%), with other provinces ranging from 8% to 13%. Including furniture as a part of rent is most common in the territorial capitals (14%) and Newfoundland and Labrador (9%).



Turning to the prevalence of inclusions by dwelling characteristics, Table 2 provides an overview of the percentage of renters whose rent comprises specific inclusions. Dwelling characteristics include dwelling type, the number of bedrooms, dwelling condition and whether the dwelling is SAH.

Utilities are more frequently included in rent for apartments, dwellings with fewer rooms, dwellings not requiring repairs beyond regular maintenance, and SAH. The inclusion of utilities in rents is more prevalent for apartments—which account for two-thirds of rented dwellings across Canada—than in other types of dwellings. Apartments in buildings with five or more storeys stand out in terms of their substantially higher inclusion rates for electricity (47%), fuel-based utilities (35%), and water and other municipal services (85%). In terms of unit size (i.e., number of bedrooms), the inclusion of utilities is more prevalent in smaller than in larger units and, to a far lesser degree, more prevalent in SAH.

In terms of other common inclusions, such as appliances, parking and air conditioning, trends vary by housing situation. The inclusion of appliances, such as stoves and refrigerators (the CHS questionnaire examples provided to respondents), is higher among apartments in buildings with five or more storeys (75% compared with 58% across all rented dwellings), dwellings with no bedroom (e.g., bachelor suites) (75%), dwellings with one bedroom (67%) and dwellings not requiring repairs (60%). Air conditioning is similarly more likely to be included in rent for apartments in buildings with five or more storeys (28% compared with 18% across all rented dwellings) and dwellings not requiring repairs. By contrast, the inclusion of parking in rent is least common for apartments in buildings with five or more storeys and dwellings with fewer bedrooms. Parking is also more likely to be included in rent for dwellings not requiring repairs and not considered SAH.

Finally, other inclusions, such as Internet, cable and furniture, are generally more prevalent in single-detached dwellings, dwellings with four or more bedrooms, dwellings not requiring repairs and dwellings not considered SAH.



Rental costs and the role of inclusions

Having explored the prevalence of rental inclusions, this paper now addresses key differences in rental costs across inclusions. This section is subdivided into two parts. The first provides brief overarching summary statistics of rental costs across housing characteristics. The second uses multivariate analyses and studies the association between housing characteristics and monthly rent paid, holding other included variables constant.

The duration of residence matters for rental prices since they are more nominally rigid in the absence of tenant turnover (Miceli and Sirmans 1999; Genesove 2003). This is because rental prices typically rise more between tenant contracts than via yearly increases in rent for long-term tenants.^Note Consistent with this trend, rental costs are negatively correlated with longer duration of residence. The average Canadian rental cost for dwellings rented within the last two years is $1,360, compared with $840 for dwellings that have had the same tenants for 10 or more years. Moreover, the non-linearity of duration of residency (i.e., substantially higher prices for shorter rental durations with diminishing differences by residency duration over time) plays an important role in explaining the substantially higher rental costs of more recently leased dwellings.

SAH similarly stands out as distinguishing generally less expensive subsidized housing from rented dwellings at market rates. Across Canada, the average and median monthly costs of SAH dwellings ($570 and $505, respectively) are roughly half those of dwellings that do not qualify as SAH.

Table 3 provides mean, median, and 25th and 75th percentile monthly rental costs across several dwelling characteristics for both the entire sample and a restricted sample that approximates market rates. The restricted sample, which excludes SAH and dwellings that have been rented for two or more years, provides approximations of market rates commonly reported in the housing literature. Average rental costs are higher across all categories for the restricted sample.

Before the paper delves into differences in rental costs by rental inclusion, it is important to contextualize rent variations across several other housing characteristics. Location, duration of residence, dwelling type, the number of bedrooms and dwelling condition, as well as whether the dwelling is considered SAH, all affect housing costs borne by renters. Though these are all determinants of rental costs in the multivariate analysis as shown in Table 4, provincial, municipal and neighbourhood variations are striking. For example, the median Canadian rented dwelling cost for renters having resided in the dwelling less than two years ($1,225) differs considerably from the median cost for the same renters in Toronto ($2,100). Percentile differences in Table 3 attest to the variability of costs by housing characteristics. Despite this finding, geographic specificities are not the focus of this study beyond acting as control or comparison variables in the subsequent multivariate analyses.

Dwelling types and dwelling size, measured as the number of bedrooms, similarly matter in terms of housing costs. Single-detached dwellings, though the priciest per month on average ($1,360), have a lower median cost ($1,140) than apartments in buildings with five or more storeys ($1,250). The higher prices for apartments in buildings with five or more storeys largely reflect that they are predominantly centrally located within metropolitan areas and are pricier because of their downtown location. As anticipated, monthly rent is lower for dwellings with fewer bedrooms. Rented dwellings with two bedrooms (40% of rented dwellings) or one bedroom (33% of rented dwellings) respectively cost $1,110 and $950 monthly on average. Dwellings requiring greater repairs are expectedly less expensive.

Counterintuitively, the inclusion of certain utilities in rent is correlated with lower rent, and this is true of average and median rents across all utilities in the restricted sample. Although one may expect property owners to charge a premium for rental inclusions to cover their costs, not including electricity is associated with an increase in the monthly cost of the average rented dwelling by $50, and $70 for water and other municipal services (or $40 and $90, respectively, in the restricted market rate sample). As explored later in the multivariate analysis, this finding partly reflects differences in housing characteristics. However, it may also be attributable to unobserved factors, such as dwelling quality.

As expected, the inclusion of air conditioning or appliances results in substantially higher average rental costs. However, while the average cost of rented dwellings with inclusions other than utilities is consistently higher for the overall sample, this is not true for the restricted market rate sample. The high degree of variability in rental costs observed across dwelling characteristics suggests that multivariate analyses are required to better understand the association between inclusions and rental costs.



Table 4 shows these multivariate analyses. They use hedonic pricing models that resemble existing estimation techniques used to estimate the rental costs component of Statistics Canada’s Consumer Price Index (Keshishbanoosy and Taylor 2019). Hedonic pricing models are a revealed preference method of estimating the value of a specific good (e.g., housing) as determined by its constituent characteristics and the sum of their respective contributory values.^Note

The hedonic models in this study estimate monthly rental costs using linear regression models that include a large set of covariates. Nevertheless, given the absence of variables specifying the age of the dwelling—as well as unobserved characteristics such as maintenance, insulation, soundproofing and construction quality, among others—it should be kept in mind that the resulting models are still subject to omitted variable bias.^Note Therefore, regression results are best interpreted as reflecting conditional correlations rather than causal impacts.^Note

Table 4 includes three models that differ by locational control variables. Variances across models largely reflect alterations to the level of geographic control variables. Model 1 uses regional controls,^Note Model 2 uses more detailed census division and census subdivision controls, and Model 3 uses even more granular regions determined by the first three characters of respondents’ postal code (i.e., forward sortation area). The increased goodness of fit when using more granular regional controls, as measured by the adjusted R-squared, testifies to the explanatory value of more detailed geographic controls. Moreover, by accounting for differences across municipalities, smaller geographies and neighbourhoods, models 2 and 3 yield statistically significant covariates that were previously statistically insignificant when solely controlling for aggregate regions. The importance of accounting for municipal- and neighbourhood-level characteristics when studying rental costs underscores the shrewdness of the well-known real estate adage: “Location! Location! Location!”

Before the paper turns to the link between rental costs and rental inclusions, it is worth examining several dwelling characteristics that constitute prototypical determinants of monthly rental costs. These act as crucial control variables in studying the unique impact of rental inclusions, holding these dwelling characteristics constant. In terms of dwelling type and holding all other variables constant, there is no statistically significant difference between single-detached housing and apartments in buildings with five or more storeys in models 2 and 3.^Note All other dwelling types are less costly.

Duration of stay is another crucial covariate. Model 3, which uses the most detailed geographic controls, suggests that households that have lived in their dwelling for less than a year pay on average $356 more per month in rent compared with renters who have lived in their dwelling for 10 years or more. Every increase in the duration of stay corresponds to a decrease in monthly rent paid. In the case of respondents reporting having “always lived here,” coefficients are not statistically significant.

Rental costs similarly vary by number of bedrooms, condition of the dwelling and whether the dwelling is SAH. Across all multivariate models, renters are expected to pay an average of slightly over $200 per additional bedroom. In line with expectations, housing in better condition typically costs an average of $85 to $90 more per month depending on whether the rental dwelling requires minor or major repairs. Expectedly, SAH is on average less expensive by over $400 per month compared with dwellings not considered SAH, according to all three models.

In terms of rental inclusions, a series of binary variables captures the inclusion of 10 categories of amenities (i.e., undertake the value of 1 if included or 0 otherwise) on rental costs. While a number of these selected inclusions are not statistically significant in Model 1, several are statistically significant when accounting for more disaggregated locational controls in models 2 and 3.^Note

When binary variables are used for each rental inclusion type, the results show significant differences in cost despite holding all else constant. The inclusion of air conditioning, parking and appliances is each positively correlated with higher monthly rents paid. According to Model 3, the inclusion of air conditioning accounts for the largest increase in monthly rent ($205), while the inclusion of parking and the inclusion of appliances are associated with $42 and $46 increases, respectively.

The inclusion of electricity in rent increases the average rental cost by $34 per month (though statistically insignificant in models 1 and 2). Other types of inclusions not explicitly listed in the survey are similarly tied to an increase in rent by $158 per month on average.

Counterintuitively, the inclusion of water and other municipal services and the inclusion of furniture are tied to decreases in monthly rent ($39 and $110, respectively, according to Model 3). In the case of included furniture, this seemingly implausible result is possibly attributable to furniture being included in rent for short-term rentals charging a discounted rental cost. However, causal explanations of these trends are beyond the scope of this study.

The inclusion of fuel-based utilities, Internet and cable is statistically insignificant, holding all other factors constant.



So, beyond differences across dwellings, is comparing rental costs by region a case of comparing proverbial apples and oranges? Analyses of rental cost differences across regions typically focus on market factors such as net migration, vacancy rates and other factors to study potential gaps in supply matching demand (CMHC 2023). Few researchers, if any, have studied provincial rent differences linked to distinct compositional characteristics of dwellings.

Table 5 provides an example of decomposition analysis applied to provincial differences in average rental costs. British Columbia, Ontario and Quebec are selected because of their larger sample sizes. The Oaxaca–Blinder twofold decompositions (Blinder 1973; Oaxaca 1973) depict the portion of the provincial difference between average costs that is explained by dwelling characteristics. As a counterfactual modelling method, Oaxaca–Blinder decompositions provide valuable insights into the proportion of the difference in average rental costs that would be explained if provinces were to have the same rental pricing structure by dwelling characteristics.

Rental inclusions are a valuable source of information to make rents comparable across provinces. Table 5 results show that the inclusion of air conditioning and the inclusion of appliances explain around 7% and 8%, respectively, of the difference in average rental costs between Ontario and Quebec.

Similarly, the lower rate of inclusion of appliances in Quebec explained around 11% of the difference in average rents between British Columbia and Quebec. While differences attributable to air conditioning are minimal between the two provinces, the overall results further suggest that rental inclusions matter when comparing rents across regions.

Interestingly, the overall explained difference in rents in British Columbia and Ontario is negative. This finding can be interpreted as provincial differences in average rental costs increasing (as opposed to decreasing) in the counterfactual scenario where both provinces had the same rental pricing structure by dwelling characteristics. Holding other variables constant, accounting for the inclusion of air conditioning would widen the interprovincial rent gap between British Columbia and Ontario from approximately $80 to $129. These findings support the need to consider rental inclusions when comparing rental costs.



Conclusion

Accounting for rental inclusions provides valuable insight into housing decisions and the rental costs borne by Canadian renters. While rental costs are amply debated in relation to housing affordability, commonly cited estimates seldom provide contextual details concerning housing characteristics and rental inclusions. Using the 2021 CHS, this study finds that rental inclusions vary substantially across dwelling characteristics and regions, with the latter stressing the spatial elements to housing costs. This analysis highlights the incidence of inclusions across Canadian rental markets and the need for more granular comparisons of rental cost data.

As for other goods and services, product differentiation matters in rental housing markets. As one salient finding from this study suggests, accounting for the inclusion of air conditioning and appliances explains 8% and 7%, respectively, of the difference in average rents between Ontario and Quebec. By highlighting the prevalence of various rental inclusions and their ties to rental costs, this study contributes to a growing literature on housing affordability and the comparability of housing costs.

Findings suggest future research on housing affordability would benefit from factoring in rental inclusions. The failure to consider rental inclusions could lead to equating heterogenous housing situations and thereby hinder the validity of rental cost comparisons. Moreover, given the rising proportion of condo buildings built (Statistics Canada 2022) and the higher propensity for such units to include additional amenities, the need to consider such differences is likely growing. Future data collection on rental housing could also benefit from a broader set of rental inclusion variables (e.g., in-building or in-suite laundry and gym access) that differentiate rental dwellings.

Housing studies also stand to benefit from more disaggregated findings by dwelling characteristics and location. Models using more detailed dwelling and locational information, in particular municipal and neighbourhood distinctions, yield substantially higher explanatory value. Additional dwelling characteristics (e.g., age of dwelling, square footage and neighbourhood amenities) and geographic detail—alongside studies of specific regions such as pricier rents in the territories, Toronto and Vancouver—would provide additional insights for current housing policy debates.

References

Beaumont, J.-F., Bocci, C., Fonberg, J. and Schellenberg, G. (2021). Measuring social capital at the neighbourhood level: Experimental estimates of sense of belonging to the local community measured at the census tract level. Statistics Canada.

Blinder, A. S. (1973). Wage discrimination: Reduced form and structural estimates. The Journal of Human Resources, 8(4), 436-455.

Canada Mortgage and Housing Corporation [CMHC] (2022). Methodology for rental market survey.

Canada Mortgage and Housing Corporation [CMHC] (2023). Rental market report.

Canadian Broadcasting Corporation [CBC] (2022). Average rents in Canada soar above $2K for first time ever, new data suggests. CBC News.

Clair, A., Reeves, A., Loopstra, R., McKee, M., Dorling, D. and Stuckler, D. (2016). The impact of the housing crisis on self-reported health in Europe: multilevel longitudinal modelling of 27 EU countries. European Journal of Public Health, 26(5), 788-793.

Elder, T. E., Goddeeris, J. H., and Haider, S. J. (2010). Unexplained gaps and Oaxaca–Blinder decompositions. Labour Economics, 17(1), 284-290.

Fonberg, J. D. and Schellenberg, G. (2019). Canadians’ satisfaction with their housing: Highlights from the 2018 Canadian Housing Survey. Statistics Canada.

Genesove, D. (2003). The nominal rigidity of apartment rents. The Review of Economics and Statistics, 85(4), 844-853.

Jann, B. (2008). The Blinder–Oaxaca decomposition for linear regression models. The Stata Journal, 8(4), 453-479.

Keshishbanoosy, R. and Taylor, L. (2019). New approach for estimating the rent component of the Consumer Price Index. Statistics Canada.

Mason, K. E., Baker, E., Blakely, T. and Bentley, R. J. (2013). Housing affordability and mental health: Does the relationship differ for renters and home purchasers? Social Science & Medicine, 94, 91-97.

Miceli, T. J., and Sirmans, C. F. (1999). Tenant turnover, rental contracts, and self-selection. Journal of Housing Economics, 8(4), 301-311.

Oaxaca, R. (1973). Male-female wage differentials in urban labor markets. International Economic Review, 14(3), 693-709.

Statistics Canada (2022). To buy or to rent: The housing market continues to be reshaped by several factors as Canadians search for an affordable place to call home. Statistics Canada.

Stick, M., Schellenberg, G. and MacIsaac, S. (2023). The neighbourhood ties of long-term residents in lower-income neighbourhoods. Statistics Canada.

Yun, T. (2022). Average rent in Canada exceeds $2,000 per month: Report. CTV News.

Zumbro, T. (2014). The relationship between homeownership and life satisfaction in Germany. Housing Studies, 29(3), 319-338.