Home » Misinterpreting the Market: A Methodological Review of the Flawed and Misleading August and St. Hilaire Study on Rental Housing in Toronto

Misinterpreting the Market: A Methodological Review of the Flawed and Misleading August and St. Hilaire Study on Rental Housing in Toronto

Michael Brooks, Ph.D, CEO, REALPAC & James Lougheed

Executive Summary

This report provides a comprehensive analysis of the 2025 study “Financialization, Housing Rents, and Affordability in Toronto” by Dr. Martine August and Chloe St-Hilaire (the “August study”). The August study is fundamentally flawed, with conclusions unsupported by its own methodology or data, and is overshadowed by a strong risk of confirmation bias.

The August study’s central claim – that “financialized” landlords are uniquely responsible for charging higher rents and driving unaffordability in the Greater Toronto Area (GTA), collapses under scrutiny.

Several critical defects have been identified:

Misattribution of Cause: The August study fundamentally misattributes the predictable outcomes of Ontario’s legislated, two-tier rent control system to the behaviour of a specific landlord class. On the contrary, the observed rent gaps are a direct consequence of government policies like vacancy decontrol, new-build exemptions, and permitted above guideline rent increases, which apply equally to all landlords, rather than to a unique strategy of “financial” owners.
Flawed Core Metric: The headline-grabbing “44% rent premium” is an artifact of a statistically invalid comparison. By contrasting asking rents for vacant units with the CMHC average for all occupied units (the vast majority of which are under long-term, rent-controlled leases), the August study produces an exaggerated and misleading gap more related to a huge spike in demand from permitted immigration during a short period of time, rather than unilateral actions of a few owners in the GTA. This “turnover gap” was a well-documented market-wide feature in the August study’s timeline, not a new discovery.
Critical Omitted Variables: The August study’s regression model fails to control for the most basic, universally accepted drivers of rent, such as building age, capital expenditures, unit size, location, and amenities. The “financial landlord” variable is thus a mere proxy for a bundle of unmeasured quality and investment characteristics, rendering the conclusion that ownership causes higher rents a classic correlation-causation fallacy.
Confirmation Bias. When viewed in the context of Dr. August’s broader body of work, which advocates for the “definancialization” of housing, these methodological choices appear to form a pattern consistent with confirmation bias: a political belief presented as objective research, structured to affirm a pre-existing narrative, rather than to test a hypothesis impartially.

These are not minor errors; they are fatal flaws that invalidate the August study’s central thesis. Moreover, the methodological choices adopted for the August study are consistent with confirmation bias, producing misleading narratives that further undermine the credibility of the August study’s conclusions.

Section 1: The Foundational Flaw: Mistaking Legislative Rules for Landlord Behaviour

The most significant and disqualifying defect in the August study is its failure to properly account for the legislated structure of Ontario’s rental market. The August study attributes rent differentials to landlord type (i.e., “financialization”) when they are, in fact, a direct and predictable outcome of landlord opportunity, created and governed by provincial rent control legislation.¹ The August study’s conclusions are therefore built on a fundamental misattribution of cause.

The Government-Designed Two-Tier System

Ontario’s rental housing market has never operated as a single, homogenous system. For decades, it has been a two-tier market, with distinct rules governing different classes of rental units. This structure, not landlord type, is the primary determinant of the rent variations the August study observes but misinterprets.

Vacancy Decontrol: The cornerstone of this system is “vacancy decontrol,” introduced in the 1997 Tenant Protection Act.¹ This policy, which Dr. August herself has previously identified as a key catalyst for real estate investment, allows any landlord, regardless of ownership structure, to reset the rent of a unit to the prevailing market rate once it becomes vacant. This creates an inherent and unavoidable gap between the below-market rents paid by long-term, “sitting” tenants and the market-rate rents advertised for newly available units. The August study fails to treat this as a universal market feature established by law, and instead frames the resulting rent gap as a behavioural choice unique to one class of owner.
The Post-November 2018 Exemption: A second critical legislative feature is the rule exempting any unit first occupied after November 15, 2018, from annual rent increase guidelines. New construction, which is disproportionately financed and developed by larger, well-capitalized entities (including those the August study labels “financial”), operates under a completely different legal and financial framework than the older, rent-controlled stock. By failing to distinguish between capped and uncapped suites in its dataset, the August study commits a fatal methodological error, comparing units governed by entirely different sets of rules and attributing the resulting difference to the owners’ corporate structure.
Above-Guideline Increases (AGIs): The August study fails to control for Above-Guideline Increases (AGIs), a legislated mechanism allowing any landlord to apply for rent increases above the annual guideline to recoup costs for significant capital expenditures, such as major repairs or renovations. Buildings with AGIs are, by definition, properties that have received recent, significant investment. Comparing their rents to buildings that have not received such investment and attributing the entire difference to “financialization” is illogical, ignoring the direct link between capital investment and legally permitted rent adjustments.

The August study is not, as it claims, a critique of landlord behaviour; rather, it is effectively an unstated and misdirected critique of government policy. The August study observes rent gaps that are the direct, legislated outcomes of vacancy decontrol, new-build exemptions, and AGI provisions – regulations that apply to all landlords. By labelling these outcomes as a product of “financialization,” the August study deflects from the policy choices that created the market structure and instead assigns blame to a specific group of participants operating entirely within the established rules.

Section 2: The Unsound Comparison: Deconstructing the “Rent Premium” Metric

The August study’s headline-grabbing claim of a “44% premium” charged by financial landlords is an artifact of a deeply flawed and misleading comparison.By comparing the asking rent for a small sample of currently vacant units to the Canada Mortgage and Housing Corporation’s (CMHC) average rent for all occupied units, the authors construct a metric that is guaranteed to produce an exaggerated result during a period of high demand caused by a spike in immigration. This methodological choice may serve a rhetorical purpose but lacks analytical validity.

Comparing Apples to Oranges

The CMHC’s “average rent” data is a composite figure that overwhelmingly reflects the rents of long-term, occupied units. In a rent-controlled market like Toronto’s, this average is heavily weighted by tenants paying below-market rates, established years or even decades prior.In contrast, asking rents reflect the current market-clearing price for the small fraction of units that are vacant and available for lease at a given time.

A significant gap between these two figures is not a discovery; it is a mathematical certainty in any market with rent control, low vacancy, and rising demand. CMHC itself documents this phenomenon, referring to it as the “turnover rent gap.” Indeed, CMHC’s recent reports for Toronto itself have quantified this market-wide gap, noting it reached 44% in 2024. CMHC correctly attributes this gap to tight market conditions and the legislated incentive for all landlords to raise rents to market levels upon unit turnover. The August study takes this known, universal market dynamic and presents it as a unique and predatory behaviour of one specific ownership class.

Contextualizing the “Premium”

Even if one were to accept the August study’s flawed metric, the marginal difference between the so-called “financial” landlord premium (44%) and the “non-financial chain” landlord premium (30%) is only 14 percentage points.¹ Is that difference based on other unit characteristics the authors did not control for? The narrative that financial landlords are in a class of their own is not supported by the August study’s own data. A far more plausible explanation for this smaller, secondary gap, is that it is entirely accounted for by the August study’s other methodological flaws, namely the failure to control for the fact that financial firms tend to own newer, higher-quality, better located and more recently renovated buildings.

The August study also overlooks that the selected period of 2022-2024 coincides with unprecedented market conditions, record immigration, post-pandemic housing shortages, high construction costs, and surging rental demand. These macro-economic pressures universally incentivize rent increases across all landlord types. By failing to differentiate these contextual factors, the August study incorrectly attributes broader market-driven rent increases to financial landlords alone, and fails to warn the reader that these rent increases were completely unique over a 25-year history in the City of Toronto. With rents now declining in the GTA, one might reasonably ask: are financialized landlords now to be solely credited for leading in rent reductions to attract tenants?

A researcher seeking to genuinely isolate the effect of ownership would compare like-for-like units (e.g., asking rents in financial vs. non-financial buildings of the same age, quality, and location) or track same-unit rent changes before and after an acquisition. The August study’s choice to instead use a comparison that conflates market trends, the effect of rent control on sitting tenants, and unit turnover, maximizes the numerical size of the “premium.” This creates a dramatic headline figure but tells us nothing meaningful about the independent effect of ownership.

This choice of metric suggests the primary goal was not to produce an accurate measure, but to generate a large, alarming number that would support a pre-existing narrative.

Section 3: The “Black Box” Regression: A Cascade of Omitted Variables

The August study employs a multiple linear regression model to assert that “financial ownership was the strongest predictor for higher rents”.⁶ However, this model is critically compromised by omitted variable bias. It fails to include controls for the most fundamental and widely accepted drivers of rental prices. As a result, the “financialization” variable does not measure a unique ownership effect; it simply acts as a proxy for a bundle of unmeasured quality, location, and investment characteristics that are the true drivers of higher rents.

The Standard for Housing Price Analysis

Academically rigorous analysis of housing prices relies on a tool known as a hedonic price model. This type of model seeks to explain the price of a heterogeneous good, like a house or apartment, by breaking it down into its constituent characteristics and estimating the value of each one. A standard hedonic model for rental prices in a market like Toronto would, at a minimum, include variables for a unit’s physical attributes, its amenities, and its location. For example, proximity to the downtown or a subway station may add $250 a month to the rent payable by a new tenant.

Systematic and Consequential Omissions

The August study’s regression model is notable for what it omits. There is a long list of “classic rent drivers” missing from the analysis. The absence of these variables is not a minor oversight; it is a fatal flaw that renders the model’s conclusions invalid. Key omitted variables include:

Building Age and Quality: Newer buildings (often classified as Class A) command higher rents than older buildings (Class B and C) due to modern construction, superior building systems, and more desirable finishes.Financial firms disproportionately own newer Class A apartment towers. By failing to control for building age, the model wrongly attributes the higher rent of a new building to its owner’s financial structure rather than to its newness.
Capital Expenditures and Renovations: Buildings that have undergone significant recent capital upgrades, such as new lobbies, windows, elevators, or plumbing stacks, command higher rents. This is the very basis for the legislated AGI process. Research confirms a positive relationship between capital expenditures and property performance. Even August’s own theoretical framework discusses “value-add repositioning” through renovation, yet her quantitative model fails to measure or control for it.
Amenities: The presence of amenities like in-suite laundry, gyms, swimming pools, concierge services, and dedicated parking has a significant, quantifiable impact on rental value. Larger, professionally managed buildings, the type most often held by institutional owners, are far more likely to offer these features. The August study’s failure to include these variables means their price effect is wrongly shifted to the “financial landlord” variable.
Unit Size (Floor Area): While the August study includes the number of bedrooms, it omits the actual floor area in square feet. This is a primary determinant of rent that is not fully captured by bedroom count alone.
Location: The August model also omits crucial location variables like proximity to subway stations or the central business district, which are classic drivers of rent in Toronto.

The following table starkly illustrates the inadequacy of the August model compared to what would be considered a standard, academically defensible approach.

Variable	August & St-Hilaire Model (2024)	Standard Hedonic Model
Landlord Type (Financial, Chain, etc.)	✓	✓
Unit Size (Bedrooms)	✓	✓
Building Class (A, B, C)	✓	✓
Disadvantaged Neighbourhood Flag	✓	✓
Building Age	X	✓
Rent Control Status (Pre/Post 2018)	X	✓
AGI Status	X	✓
Unit Floor Area (sq. ft.)	X	✓
Capital Expenditure per Unit	X	✓
In-Suite Laundry	X	✓
Building Amenities (Gym, Pool, etc.)	X	✓
Proximity to Transit	X	✓

This cascade of omissions leads to an inescapable conclusion: the August study does not prove that financial landlords charge more for the same apartment; it merely shows that more expensive apartments are more likely to be owned by financial landlords.

This is a classic correlation-causation fallacy.

Institutional investors, with access to large pools of capital and a mandate for stable, long-term returns, are rationally drawn to higher-quality, lower-risk, well-located, professionally manageable assets. These asset characteristics are the actual drivers of higher rents. Because the August study’s regression model omits these key characteristics, the “financial landlord” variable becomes a statistical proxy for this entire bundle of unmeasured, rent-driving attributes. The model is observing a selection effect (who buys what) but is intentionally misinterpreting it as a treatment effect (what the owner does). The leap therefore to claiming that ownership causes the higher rent is empirically unsupported.

Section 4: The Fallacy of the Monolith: Portfolio Composition vs. Predatory Practice

A central pillar of the August study’s narrative is the creation of a single, unified category of “financial landlord.” The August study has defined this label broadly to include REITs, private equity funds, asset managers, and institutional investors like pension funds. Treating such disparate entities as a homogenous class is a gross oversimplification that obscures crucial differences in investment strategy, time horizon, and risk appetite. This flawed categorization is essential to the August study’s narrative of a unified, predatory class of owner, but it does not reflect market reality.

Diverse Entities, Diverse Strategies

The entities grouped under the “financial” umbrella pursue fundamentally different goals and operate under different constraints, leading to varied approaches to asset management.

Real Estate Investment Trusts (REITs): As publicly traded entities, REITs are generally long-term holders of property. Their primary mandate is to provide stable, income-producing assets to generate consistent dividends for a broad base of shareholders. REITs typically distribute all of their taxable income to avoid taxation at the higher level, which limits the capital available for high-risk, aggressive repositioning strategies. They are often more risk-averse, seeking stabilized, high-quality (Class A) properties that generate reliable cash flow.
Pension Funds: With very long-term liabilities matching the retirement needs of their members, pension funds are among the most conservative institutional investors. They seek stable, inflation-hedged returns and typically invest in or partner on “core” assets: high-quality, well-occupied buildings in prime locations.¹ Their investment horizon can span decades.
Private Equity Firms: In contrast, private equity funds often operate with much shorter time horizons, typically aiming to exit an investment within a 3- to 7-year window. Their model is frequently based on pursuing higher-risk, higher-return “value-add” or “opportunistic” strategies. This can involve acquiring underperforming or distressed assets, undertaking intensive renovations and repositioning, and then selling the stabilized property to a longer-term holder (like a pension fund or REIT) to realize a capital gain.

To treat these distinct actors as a single, monolithic entity is to ignore the fundamental structure of the institutional real estate market.

Portfolios, Not Practices

Financial owners, as a group, simply own more of the newer, higher-class buildings.This is the central point: their aggregate portfolio has a higher average rent because it is composed of more expensive assets. This is a reflection of investment strategy and capital availability, not a uniform practice of charging more for an identical unit.

An institutional investor has the capital to acquire a new, 500-unit downtown high-rise building, while a small-scale independent landlord typically owns an older, smaller walk-up building in a peripheral neighbourhood. The high-rise will command higher rents due to its age, location, quality, and amenities, regardless of whether its owner is a pension fund, a REIT, or a private company.

The “financialization” label, as used by the August study, conflates the act of owning expensive buildings with the act of making buildings expensive. By lumping all institutional investors together and comparing their portfolio’s average rent to the city-wide average, the August study is merely observing that a portfolio of more expensive buildings has a higher average rent than a portfolio of less expensive buildings. This tautological finding is then presented as evidence of a unique behavioural trait (“charging more”), when it is in fact a simple reflection of portfolio composition and selection bias.

Section 5: A Pattern of Bias: Framing the Research as a Foregone Conclusion

The methodological flaws detailed in the preceding sections are not isolated or random errors. They form a consistent pattern that points toward a significant risk of confirmation bias, where research is designed not to impartially test a hypothesis, but to validate a pre-existing ideological position. This is a critical consideration in evaluating the August study’s credibility and directly addresses the objective of determining whether the article should be substantially discounted.

The A Priori Belief System

Dr. August’s extensive body of work, particularly her 2022 report for the Office of the Federal Housing Advocate, establishes a clear and unwavering ideological framework. In this work, housing is framed as a “human right” that is structurally and irreconcilably opposed to its function as a “financial asset”. Financial firms are defined by their “fiduciary responsibility to maximize value for shareholders,” a duty that is presented in Dr. August’s report as inherently antithetical to tenant well-being and affordability. The report’s recommendations are not for market reform or improved regulation, but for the outright “definancialize[ation] of ownership,” including the expropriation of housing owned by financial firms. This is not a neutral or empirical starting point; it reflects a deeply held conviction that private institutional ownership of rental housing is illegitimate.

Connecting Belief to Methodological Choice

This pre-existing belief system provides a powerful lens through which to understand the otherwise inexplicable methodological “choices” made in the Toronto rent study.

Choice of a Flawed Metric: The decision to compare asking rents on vacant units to the average rent of all occupied units may not have been an oversight. It may have been a choice that guaranteed a large, headline-worthy “premium” that aligns perfectly with a preferred narrative of exploitation and price gouging.
Choice to Omit Key Variables: The systematic exclusion of building age, quality, capital investment, and amenities may have seemed necessary to advance the August study’s thesis. Including these standard control variables would have demonstrated that these factors, not ownership type, explain the rent differences, thereby invalidating the desired conclusion. If data was not available for an exhaustive analysis, the limitation should have been identified.
Choice to Obscure Statistical Insignificance: The August study fails to report confidence intervals for the trivial 0.04 percentage point difference in quarterly rent change between “financial” and “chain” landlords. This difference (5.03% vs. 4.99%) is almost certainly statistically insignificant, meaning it is indistinguishable from random noise. Reporting this would have undermined the claim that financial landlords “lead the industry in raising rents”.
Choice of Rhetorical Framing: The language used in the August study and its promotion reflects that of an activist campaign, not a dispassionate scientific inquiry. Phrases such as “proof of gouging,” “eviscerate housing affordability,” and “systematically making housing less affordable” are assertions of motive and causation that the flawed data cannot possibly support.

The following table deconstructs the August study’s key public claims, contrasting them with the underlying data and offering a more plausible, evidence-based explanation.

Newspaper Claim	The August Study’s Underlying Data	The Evidence-based Explanation
“Financial landlords charge a 44% rent premium.”	The premium for non-financial “chain” landlords is 30%. The marginal difference is only 14 points.	The 14-point difference is attributable to financial firms owning newer, higher-quality, and more renovated buildings—factors the August study failed to control for. The overall “premium” is an artifact of comparing asking rents to average occupied rents.
“Financial landlords lead the industry in raising rents.”	Quarterly rent change was 5.03% (financial) vs. 4.99% (chain). A difference of 0.04%.	This microscopic difference is statistically indistinguishable from zero and is well within the margin of normal sampling error and noise from changing unit mix.
“Research proves investor pressure drives rent hikes.”	The regression model contains no variables for investor returns, leverage, debt service, or any other measure of “pressure.”	This is a conclusion asserted without any supporting evidence in the model. Causation is inferred from a flawed and spurious correlation.

The pattern seems clear: at every stage, from the construction of the core metric to the selection of regression variables and the framing of the results, choices were made that served to amplify the apparent negative effect of “financialization” and obscure countervailing evidence. This consistent pattern strongly supports the conclusion that the August study suffers from profound confirmation bias and was designed to reach a foregone conclusion.

Section 6: An Evidence-Based Alternative: The Real Drivers of Toronto’s Rental Market

To effectively rebut the August study’s flawed narrative, it is not enough to deconstruct its errors. It is essential to construct a coherent, evidence-based alternative explanation for Toronto’s housing affordability challenges. The data indicates that the primary cause is not a specific class of landlord, but rather the fundamental, structural drivers of the market: chronic supply constraints created by decades of public policy at all levels of government.

The Core Problem: A Chronic Supply-Demand Imbalance

For years, population growth in the Greater Toronto Area has consistently and dramatically outpaced the construction of new housing units.³⁴ This fundamental imbalance between the number of people seeking homes and the number of homes available is the primary driver of price and rent escalation. When demand far exceeds supply, prices inevitably rise. This is the central economic reality of Toronto’s housing market. This was particularly true during the period selected by the August study authors (2021-2022), when immigration surged to near triple annual immigration levels, creating intense competition for scarce apartments available in Toronto.

The Policy Drivers of Scarcity

This supply crisis is not an accident of nature; it is the direct result of specific policy choices that have made it difficult, slow, and expensive to build new housing. Research from independent bodies such as the Fraser Institute and the C.D. Howe Institute has extensively documented these policy barriers.

Restrictive Zoning and Land-Use Regulation: A vast portion of Toronto’s residential land, over 60%, is zoned exclusively for single-family homes.³⁷ This “exclusionary zoning” artificially limits density, prevents the construction of “missing middle” housing like townhouses and low-rise apartments, and forces new growth into a small number of high-rise nodes or to the urban fringe.
Burdensome Development Charges and Taxes: Toronto and surrounding municipalities impose some of the highest upfront charges on new housing in North America.³⁶ These fees, including development charges, parkland levies, and community benefits charges, can add hundreds of thousands of dollars to the cost of a single new home.⁴² These costs, which have increased exponentially over the past decade, are ultimately passed on to homebuyers and renters, and they make many potential rental projects financially unviable from the outset.
Lengthy and Uncertain Approval Timelines: Navigating the municipal approvals process in the GTA is notoriously slow and unpredictable. These delays add significant risk and carrying costs to development projects, discouraging investment and slowing the delivery of new supply.

The Constructive Role of Institutional Capital

In this policy-induced environment of scarcity and high development costs, institutional investment is not the cause of the problem but a rational response to it. Far from “eviscerating” affordability, large-scale professional landlords play two crucial roles that are essential to the functioning of the rental market.

First, they provide the large-scale, patient capital necessary to undertake the complex, high-density projects that are essential for increasing supply in a land-constrained city like Toronto.⁴⁸ Second, they acquire and professionally manage an aging rental stock, much of which was built in the 1960s and 1970s that is in dire need of significant capital investment for repairs and modernization.

The narrative that blames “financialization” for Toronto’s housing woes is a convenient distraction from the difficult political choices required to fix the crisis. The real solutions, comprehensive zoning reform, reducing the tax burden on new construction, and streamlining approval processes, are politically challenging because they disrupt the status quo. It is far easier to create an external villain in the form of “financial landlords” than to confront the consequences of decades of municipal, provincial and federal policy failure and underinvestment in deeply affordable housing.

Conclusion: Focusing on Real Solutions

Blaming a vaguely defined group of “financial landlords” is a convenient distraction from the real causes of Toronto’s housing crisis: a chronic lack of supply driven by restrictive zoning, punishing development taxes, and slow approval processes. Professional housing providers, including institutional investors, are a critical part of the solution. They provide the capital needed to build new supply and to upgrade and maintain Canada’s aging rental stock.

Serious housing policy must be based on sound data and a correct diagnosis of the problem. Unfortunately, the August study provides neither. It is a disservice to the important public debate on housing affordability and should be set aside in favour of evidence-based solutions that address the true barrier to affordability: a critical shortage of housing supply.

Sources

August, M. (2022). The financialization of multi-family rental housing in Canada: A Report for the Office of the Federal Housing Advocate. Ottawa, ON: The Office of the Federal Housing Advocate.
Government of Ontario. Residential Tenancies Act, 2006, S.O. 2006, c. 17. The exemption for units first occupied after November 15, 2018, is a key provision of this Act.
Ibid. The mechanism for Above-Guideline Increases (AGIs) is established under this Act and detailed in materials from the Landlord and Tenant Board. The process is discussed in August (2022).
August, M., & St-Hilaire, C. (2025). “Financialization, housing rents, and affordability in Toronto.” Environment and Planning: Economy and Space. The 44% figure is a central claim of this study.
Various news reports covering the August & St-Hilaire (2025) study, which use phrases like “proof of gouging” and highlight the 44% premium. See, for example, reports in ca.news.yahoo.com and building.ca.
August, M., & St-Hilaire, C. (2025), as cited in news reports from the University of Waterloo and ca.news.yahoo.com.
Canada Mortgage and Housing Corporation. (2025, July). Mid-Year Rental Market Update. This report notes the gap between asking rents for vacant units and average rents for occupied units, identifying a 44% gap in Toronto for 2024.
Canada Mortgage and Housing Corporation. (2024, Fall). Rental Market Report. Provides data on average rents, which are heavily weighted by long-term tenancies.
Statistics Canada. (2021). Census of Population. Data shows that recent renter households face significantly higher shelter costs than existing renter households, illustrating the turnover gap.
City of Toronto. (2021). Inclusionary Zoning Assessment Report. Notes that asking rents for purpose-built rentals can be up to 40% higher than CMHC-reported average market rents.
Canada Mortgage and Housing Corporation. (2025, July). Mid-Year Rental Market Update.
Statistics Canada. (2021). Census of Population..
Canada Mortgage and Housing Corporation. (2025, July). Mid-Year Rental Market Update.
Lao, Y., et al. (2021). Rent Control and Rental Prices in Toronto: A Dynamic Hedonic Analysis. ResearchGate. This study employs a hedonic model to evaluate rental prices in Toronto.
Bourne, L. S., & Bunting, T. (2011). Property valuation in the City of Toronto: a regression approach. This report uses a hedonic price model and identifies key variables including accessibility to the downtown and subway stations.
He, B., et al. (2008). “Urban Location and Housing Prices within a Hedonic Model.” Journal of Regional Analysis and Policy. Discusses the use of location characteristics in hedonic models.
CMHC. (1996). House Price Indexes by City: An Assessment of the Quality of Home Owners’ Estimates. This early report discusses the methodology of hedonic regressions for housing prices.
Arbor Realty Trust. (2016). “How Building Age Can Impact Multifamily Rents.” Arbor Blog. This article discusses how rent rates vary by building vintage, with newer buildings generally commanding higher rents.
Gyourko, J., & Nelling, E. (2014). “The Impact of Capital Expenditures on Property Performance.” Journal of Property Research. Research shows a positive relationship between capital expenditures and property returns.
Statistics Canada. (2023). “The value of amenities and other non-financial inclusions in rental cost comparisons.” Economic and Social Reports. This report documents the prevalence of amenities and their impact on rental costs.
Royale Realty Brokerage. (n.d.). “The Impact of High-End Amenities on Property Value.” This article highlights how amenities like pools, gyms, and concierge services increase property value and rental appeal.
Listing2Leasing. (n.d.). “The Role of Amenities in Real Estate Rental Prices.” Discusses how amenities like fitness centers and pools can justify higher rental prices.
Found Spaces. (n.d.). “The Importance of Tenant-Friendly Amenities in Rental Properties.” Notes that amenities like on-site laundry, secure entry, and fitness centers enhance property appeal.
DelSuites. (n.d.). “Short Term Rentals Toronto.” Highlights in-suite washer/dryer as a key amenity that adds value over hotel stays.
Bourne, L. S., & Bunting, T. (2011). Property valuation in the City of Toronto: a regression approach. Identifies proximity to the subway system as a driver of price.
August, M. (2022). The financialization of multi-family rental housing in Canada. Defines REITs and discusses their legal structure and priorities.
REALPAC. (2019). White Paper on Funds From Operations & Adjusted Funds From Operations for IFRS. Provides industry standards for REIT financial reporting.
InvestNext. (n.d.). “REITs vs. Private Equity: Understanding the Key Differences.” Outlines the structural and strategic differences between REITs and private equity firms.
Ibid.
Burke, L. A. (2007), as cited in “Considering confirmation bias in design and design research” (2015). Discusses the pervasiveness of confirmation bias in various practical contexts.
Pompian, M. M. (2012). Behavioral Finance and Wealth Management. Discusses how confirmation bias leads investors to seek out information that confirms their beliefs and ignore contradictory evidence.
August, M., & St-Hilaire, C. (2024), as cited in various news reports. The promotional materials and news coverage use framing language such as “eviscerate housing affordability”.
Fraser Institute. (2025). The Crisis in Housing Affordability: Population Growth and Housing Starts 1972–2024. Documents the growing gap between population growth and housing starts in Canada.
C.D. Howe Institute. (2025). “Slowing Population Growth May Already Be Slowing Increases in Rents.” Discusses the link between population growth and rental demand.
C.D. Howe Institute. (2025). Making Housing More Affordable in Canada: The Need for More Large Cities. Argues that housing affordability has deteriorated significantly in Canada’s large metropolitan areas.
Canadian Dimension. (2024). “Zoning deregulation won’t fix the housing crisis.” Notes that in Toronto, over 60 percent of the city is zoned exclusively for single-family homes.
Fraser Institute. (2016). The Impact of Land-Use Regulation on Housing Supply in Canada. Argues that restrictive land-use regulations limit housing supply and encourage sprawl.
Fraser Institute. (2018). “‘Inclusionary zoning’ will reinforce Toronto’s exclusionary zoning policies.” Criticizes Toronto’s rigid zoning policies that restrict development.
Fraser Institute. (2019). “Toronto takes small step forward with laneway houses.” Discusses “as-of-right” zoning as a way to overcome restrictive bylaws.
Fraser Institute. (2024). Barriers to Housing Supply in Ontario. Identifies lengthy and uncertain approval timelines as a key barrier to housing development.
Storeys. (2024). “As Toronto’s Development Charges Approach A Breaking Point, Some Experts Say It’s Time For A Change.” Reports that the DC on a single-family home in Toronto is $141,139 as of September 2024, a 993% increase from 2010.
RYZ Solutions. (2024). “Under Pressure: How Rising Development Charges and Taxes Are Reshaping Canada’s Housing Future.” States that the total tax burden on new homes in Ontario averages 36% of the final purchase price.
Fraser Institute. (2025). “Ontario government will spend more for less housing.” Notes that Ontario municipalities impose some of the highest upfront charges on new housing development in Canada.
Miller Thomson LLP. (2024). “Rethinking development charges in Ontario: A path to affordable housing.” Discusses how rising DCs have increased the cost of delivering new housing.
City of Toronto. (2024). Staff Report on Purpose-built Rental Homes Incentives. Notes that high interest rates, inflation, and increasing construction costs have resulted in a significant slowdown in new residential development.
Fraser Institute. (2016). The Impact of Land-Use Regulation on Housing Supply in Canada. Identifies long and uncertain approval timelines as a major deterrent to new supply.
American Action Forum. (2025). “Primer: Institutional Investors Aren’t Ruining the Housing Market.” Argues that institutional investors add liquidity and increase rental supply.
Obiter.ai. (2022). “What can we learn from the age of Toronto’s apartment buildings?” Notes the large stock of aging rental buildings from the 1950s and 60s boom.