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  • Good intentions gone rogue: Why demand-side interventions need to be targeted and offset with supply 
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Good intentions gone rogue: Why demand-side interventions need to be targeted and offset with supply 

April 15, 2026

Mathieu Laberge — Chief Economist and Senior Vice-President, Housing Insights

Mathieu Laberge — Chief Economist and Senior Vice-President, Housing Insights

When addressing a housing affordability crisis, there is always a tug-of-war between demand- and supply-side housing interventions. 

Demand-side interventions, which directly help households secure housing, are often favoured because of their more immediate impact.  The results are easier to see and measure compared to building new homes, which take years to deliver. 

A basic principle of supply and demand shows that if demand increases without proportionate supply, prices will increase. New modeling by CMHC shows that this dynamic occurs with housing demand-side interventions. Over time, they may worsen housing affordability, instead of improving access to housing. 

One key learning from this new modeling is that while our ambitions to help Canadians find the right housing must remain a priority, the means to achieve them must be balanced: Demand-side supports must be targeted and accompanied by sufficient supply. 

How can direct support to aspiring homebuyers reduce affordability? 

Well-intentioned demand-side interventions can make housing less affordable due to pent-up demand (what economists call induced demand). 

High housing prices can delay household formation — we all know of young people staying longer at their parents’ home or friends extending apartment-sharing arrangements because they can’t afford housing on their own. 

In a more favourable housing market, these people would form their own households, but with high housing prices, they simply can’t afford to. This is called household suppression — the basis of pent-up demand. This is a well-documented phenomenon in academic literature and is also considered by other Canadian housing researchers.

A demand-side intervention would try to correct this issue by either increasing household income or reducing housing costs, enabling people to afford housing of their own. Naturally, these people would start looking for a home — this is the intent of the intervention. 

In doing so, they generate immediate new demand for housing, whereas increasing home construction takes time. This puts renewed upward pressure on prices for all households, not only those benefitting from the intervention, thus reducing affordability for those not benefitting from it. 

How can demand-side measures avoid worsening affordability?

Using CMHC models, we created 2 scenarios to illustrate how this works: 

  1. A more limited scenario: Support is provided to a smaller number of households (20% of potential buyers).
  2. A more ambitious scenario: Support is provided to more people (70% of potential buyers). 

In each scenario, Canadians benefitting from the intervention would see their monthly mortgage payment go down by about 4%. These scenarios were kept generic on purpose to avoid confusion with current policies. They are for illustrative purposes only and do not represent forward guidance, financial advice or policy recommendations from CMHC. 

Under the first scenario, 17,000 people would be able to attain homeownership. However, this number would decrease over time as additional demand from new homebuyers would put upward pressure on prices.  CMHC’s modeling shows the increase in demand from the new homeowners benefitting the intervention means every other homebuyer that doesn't qualify would face a 0.6% increase in house prices.

The estimated economic cost of this intervention would be $2.7 billion to $4.3 billion in direct spending for the intervention itself and $1.6 billion in unintended increased costs for all homebuyers that are not supported by the new intervention. 

Figure 1: Number of Households and Number of Households Becoming Homeowners over 2024 to 2030 Under the Intervention Scenario #1: Difference with the Base

Source: CMHC calculations

Number of Households and Number of Households Becoming Homeowners over 2024 to 2030 Under the Intervention Scenario #1: Difference with the Base
Year 2024 2025 2026 2027 2028 2029 2030
New households being formed relative to base 0 17,440 21,748 16,573 14,474 14,804 15,167
New households becoming homeowner relative to base 0 11,829 16,583 13,345 10,171 10,419 12,198

Figure 2: National Average House Prices over 2024-2030 under the Intervention Scenario: Difference with the Base Scenario

Source: CMHC calculations

National average house prices over 2024 to 2030 under the intervention scenario: Difference with the base scenario
Year 2024 2025 2026 2027 2028 2029 2030
National average house prices 0.00% 0.14% 0.50% 0.63% 0.60% 0.58% 0.58%

Scenario 2 shows that, under a less targeted demand-side intervention, these effects are amplified. In this case, 76,000 new households would be created at the peak, and 52,000 people would be able to access homeownership. In this case, other homebuyers would face a 2.1% increase in house prices due to the new intervention, compared to the status quo.

The full economic cost of this intervention would be $9.3 billion to $11.4 billion in direct spending for the intervention itself and $2.1 billion in unintended increased costs for all homebuyers that are not supported by the new intervention.

Figure 3: Number of Households and Number of Households Becoming Homeowners over 2024-2030 under the Intervention Scenario #2 (Aimed at a Broader Population): Difference with the Base 

Source: CMHC calculations

Number of Households and Number of Households Becoming Homeowners over 2024 to 2030 under the Intervention Scenario #2 (Aimed at a Broader Population): Difference with the Base 
Year 2024 2025 2026 2027 2028 2029 2030
New households being formed relative to base 0 61,015 76,297 58,688 51,354 52,358 53,612
New households becoming homeowner relative to base 0 47,953 52,300 44,750 38,846 40,131 39,469

Figure 4: National Average House Prices over 2024-2030 under the Intervention Scenarios: Difference with the Base Scenario

Source: CMHC calculations

National average house prices over 2024 to 2030 under the intervention scenarios: Difference with the base scenario
Year 2024 2025 2026 2027 2028 2029 2030
Policy scenario 0.00% 0.14% 0.50% 0.63% 0.60% 0.58% 0.58%
Policy scenario aimed at a broader population 0.00% 0.48% 1.78% 2.24% 2.14% 2.08% 2.08%

The bottom line for both interventions is clear: While they support access to homeownership for a select group, they impose costs on a much larger number of households. As a result, housing affordability would decrease across the board with the broader intervention, as illustrated in the graph below.

Figure 5: Price-to-Income Ratio over 2025-2030: Base Scenario Versus Intervention Scenarios1

Source: CMHC calculations

Price-to-income ratio over 2025 to 2030: Base scenario vs intervention scenarios
Year 2025 2026 2027 2028 2029 2030
Base scenario (status quo) 5.29 5.31 5.16 5.08 5.05 5.05
Policy scenario 5.30 5.34 5.20 5.11 5.08 5.08
Policy scenario aimed at a broader population 5.32 5.41 5.28 5.19 5.15 5.16

How to prevent adverse affordability impacts from demand-side interventions: Narrow targeting and proportionate supply 

CMHC’s modeling shows there are 2 ways to prevent adverse housing affordability effects from demand-side interventions.

The first one is to target interventions as strategically as possible, to those with the greatest need. This approach would limit the increase in demand and the resulting pressure on prices, while ensuring the intervention delivers the maximum social benefit.

This is exemplified in our scenarios above: The cost of scenario 1 (both in spending and in broader economic impact) is much lower than in scenario 2. This makes demand-side interventions more niche, but still relevant for supporting some of the most vulnerable populations.

The other way to mitigate the adverse effects of demand-side interventions is to match them with proportionate supply, to offset the impact of increased demand on prices. The broader and less targeted the intervention, the greater the increase in housing starts needed to offset the adverse impact.

In the case of scenario 1 (limited intervention), 7,800 new housing starts annually would help offset the impact of the intervention. For scenario 2 (broader intervention), 28,000 new housing starts annually would help offset the impact of the intervention. At the current pace of housing starts, these represent annual increases of roughly 3% to 11%. This aligns with our current estimated supply gap.

Bottom line: It’s all a question of balance and restraint 

The analysis above is key to understanding how to address the Canadian housing crisis. Each intervention tool has its own benefits and drawbacks. Demand-side interventions have the benefit of providing immediate relief, but can still harm housing affordability in the long term if not used carefully. Supply-side interventions are slow to impact affordability given the time it takes to build housing, but they positively impact a much broader range of households. The overarching conclusion is clear: They both go hand-in-hand.

This article includes contributions from Pierre-Luc Deslauriers.

Methodological notes

For details on CMHC’s models used in this analysis, see the Integrated Housing Model (IHM): Technical documentation (PDF).

Footnotes

1 The chart shows that affordability improves between 2025 and 2030 across all scenarios. This improvement is mainly driven by slower price growth, largely due to reduced population growth. In all cases examined in the study, demand side interventions worsen affordability relative to the baseline scenario, with a more pronounced effect when the policy applies to a broader share of potential homebuyers (70%).

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Mathieu Laberge
Chief Economist and Senior Vice-President, Housing Insights

Mathieu Laberge leads a team of experts in housing economics and insights whose work informs Canada’s efforts to address key housing issues including housing affordability.

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Date Published: April 15, 2026
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