Housing shortages in Canada

Canada faces a housing affordability challenge. For many years, housing prices and rents in Vancouver and Toronto attracted attention from all over the world. Over time, these increases came to burden many Canadians and their children. Low-income and some middle-class households struggle to even find a place to live, let alone at a price they can afford.

On a wider scale, the productivity of the Canadian economy suffers from unaffordable housing as the capacity to attract skilled workers is diminished and the young are deterred from staying in our largest cities partly because of the lack of attainable housing. And Canada’s enormous level of household debt creates a vulnerability in the event of a global economic crisis.

Challenges have become more widespread across Canada since the pandemic.

People grew tired of housing costs and long commutes, and eventually moved to other cities. For many, the ability to work remotely helped this move. This drove up house prices across Canada. Increases in demand cause higher house prices because the housing supply system takes years to adjust.

Increasing housing supply for all income levels is key to improving affordability. Since 2022, CMHC has published its estimates on how much housing would be needed to restore affordability to early 2000s levels by 2030. Our analysis helped to inform and guide policies to address the scale of the challenge.

Our past analysis showed the magnitude of the challenge to restore affordability. Publishing these results encouraged policy changes to promote housing supply. But while our previous approach to estimating how much housing is needed succeeded in encouraging change, we now need to make further changes.

Changes in our approach

First, the time it takes to get approval for and build new housing means that our 2030 timeline is no longer realistic. While building a new structure may take 1 or 2 years, getting the approvals to rezone land is a multi-year process.

To reflect these timelines, we’ll begin presenting our results on a rolling 10-year horizon. As a result, for this report, we estimate how much housing is needed by 2035. We also present our results to highlight the change in the number of housing starts required per year rather than a cumulative total. This will ease comparison with current and potential rates of housing construction.

Second, restoring affordability to levels last seen 2 decades ago isn’t realistic, especially after the post-pandemic price surge. COVID-19 significantly changed the affordability landscape across the country. In particular, Toronto and Vancouver face more structural affordability challenges that require more time to address.

As a result, we’re changing our aspiration to restoring affordability to levels seen just before the pandemic. This change also highlights how widespread the housing affordability challenge has become across Canada. This aspiration shouldn't be interpreted as an official government target. Instead, it’s a way to show how big of a challenge it is to return to affordability.

Further improvements to our approach include incorporating more feedback effects into our analysis by generating informative scenarios.

To illustrate what this means, suppose that housing supply were to increase in only 1 city so that house prices would fall. This isn’t the end of the story. Some people would move to that city from the rest of Canada to benefit from greater affordability. Effectively, demand for housing in this city would be greater than originally expected because of this influx. As a result, even more housing needs to be built to return to affordability.

Preview of results

We find that housing starts need to double over the next decade. Compared to a projected rate of about 250,000 new housing units annually until 2035, Canada needs to increase housing starts to around 430,000 to 480,000 units per year to restore affordability (depending on parameters).

This can only be possible with:

• a significantly greater workforce
• more private-sector investment
• changes in technology and productivity such as more automation and modular construction

The need to increase housing supply remains critical.

Housing affordability has come to affect almost everyone in Canada. Figure 1 and Figure 2 dig into this by showing average annual changes in house prices and rents over the past 2 decades. These are key components of any measure of affordability.

The data are split into 2 categories: pre- and post-pandemic.

Figure 1 shows increases in house prices in Ottawa – Gatineau, Montréal and Nova Scotia as well as other parts of Ontario, Quebec and British Columbia. Meanwhile, Figure 2 shows that average rents have increased across the country and to largely similar degrees in each region.

In this report, we concentrate on average affordability within regions of Canada. We don’t address how affordability varies within regions, although many households with low incomes struggle with housing costs even in regions that remain affordable on average.

Figure 1: House Prices — Average Annual Growth (%)

Source: CMHC calculations.

Note: Average annual growth rate (AAGR). House prices: price changes based on a CMHC repeat sales price index (2024 house price data is for the first 3 quarters only). This is a different price measure than forecasted in the CMHC Housing Market Outlook (HMO) publication.

Figure 2: Rents — Average Annual Growth (%)

Source: CMHC calculations.

Note: Average annual growth rate (AAGR). Rents: average rent of purpose-built private rental units (apartments and rows, all bedroom types). This is a different rent measure than forecasted in the CMHC Housing Market Outlook (HMO) publication.

House prices and rents are reported differently

The data on rents and house prices are different concepts, which complicates interpretation.

House prices are recorded when a sale takes place. As a result, house prices reflect market transactions rather than values across the entire spectrum of housing.

In contrast, CMHC data on average rents cover rents of most purpose-built rental units and not just those available for new tenants at the current market price.

Therefore, changes in home prices and rents are not directly comparable. While CMHC has started to report on rents when units are turned over to new tenants, reflecting market transactions, these are insufficient for modelling.

What is affordability?

There’s no settled definition of housing affordability but it relates housing costs to income. In housing market analysis, a common convention is to compare the monthly cost of purchasing an average home to the average or median income.

In our previous reports (PDF), we developed a comprehensive metric of homebuying costs that included criteria for qualifying for a mortgage. Unfortunately, house prices have risen so much in our most expensive cities that the average household wouldn’t qualify to buy the average home under current mortgage rules. As a result, that metric has become obsolete.

We therefore adapted how we measure homebuying affordability. We now use a more generic price-to-income ratio (or “homebuying affordability ratio”) with an adjustment factor to account for changes in mortgage rates and homeowner expenses. This allows us to better monitor homebuying affordability over time in all regions. Interpretation remains the same: the higher the ratio, the less affordable the market.

Other metrics could be used in our work, subject to data availability and whether the metrics could be integrated into our modelling framework.

Changing our aspiration for affordability

The loss of affordability over the past 2 decades has been large and is becoming larger. The supply required to return to that level of affordability would put an unrealistic strain on resources.

Training and expanding the construction workforce has been a challenge even to reach our current level of production. To improve productivity in the housing sector, Canada will need private sector capital. However, we also need to boost productivity across the whole economy. As a result, the available funds are limited.

While the results from our previous reports remain valid, we’re changing our aspiration for affordability to match pre-pandemic levels, which has several impacts.

Figure 3 highlights the substantial loss of affordability in Ontario, British Columbia, Quebec and Nova Scotia, as well as losses elsewhere, between 2019 and 2024. It also shows the levels of affordability we aim to return to in our modelling. Rather than being government targets, these illustrate what would be required to regain lost affordability.

In general, we aim to return to levels of affordability at which adjusted house prices (homebuying affordability ratios) are:

1. no higher than 30% of average gross household income; or
2. no higher than their 2019 levels, in the more unaffordable regions

This means that, in British Columbia and in parts of Ontario and Montréal, we aim for affordability levels of 2019 (higher than 30%). Many parts of Canada — the Prairies and parts of the Atlantic region — were affordable in 2019, with affordability ratios less than 30%. They’ve now breached that level. Increased housing supply will move them back to the 30% threshold.

The loss of affordability shown in this figure mostly explains our findings of where more housing supply is needed, discussed later. For example, the loss of affordability since 2019 in Montréal, Ottawa – Gatineau, the rest of Ontario and Nova Scotia leads to more housing being needed there.

Figure 3 provides our interpretation of what might be a realistic level of affordability. They’re meant to be illustrative. In turn, projected ratios for 2035 in our scenario, compared to the aspiration, is central to understanding the size of the supply gap in each region.

Figure 3: Homebuying Affordability Ratios (House Price-to-Income, Adjusted for Mortgage Rates and Homeowner Expenses)

Source: CMHC calculations.

Note: Average house price-to-average gross household income ratio, with an adjustment factor to account for interest rates (5-year fixed discounted mortgage rate) and monthly homeowner expenses (estimations of property taxes, utilities, maintenance and insurance).

* The target for the model is that, by 2035, the adjusted housing price metric should be no higher than 30% of gross household income where this is still realistic, or no higher than its 2019 level in the most expensive regions.

More detailed modelling

In this report, we provide a breakdown of results for Canada’s 6 largest cities, in addition to the results for all provinces presented in the previous reports. We also provide more detailed results on the breakdown between rental and homeownership housing.

Greater geographical detail means we need to incorporate more “feedback” effects (discussed in the introduction), which leads to our discussion of more sophisticated modelling below. In general, modelling at a more local level means that we need to consider more factors such as the impact of changing housing affordability on population mobility. Changes in patterns of housing affordability are more likely to influence households to move between Toronto and the rest of Ontario than they are to influence them to move between Ontario and British Columbia, for example.

More sophisticated modelling

In line with previous reports, we continue to advance our understanding and our modelling of the Canadian housing system. These changes are explained in more detail in a technical report published separately. We have made many model enhancements that are described in the technical report rather than here.

Our new modelling includes the effects of house price changes on:

• population mobility; and
• household formation

Incorporating these effects has many impacts, including if house prices were to fall in a city because of increased supply, then:

• Households would move there from other parts of Canada. This would lower demand in the places they left but creates further demand in the city where supply increased; and
• More households would be formed in that city as adult children leave the parental home, for example. Again, this further increases demand for housing, offsetting the original decrease in prices.

In both cases, planners need to anticipate that even more housing needs to be built as prices fall.

• Parts of Canada that have been relatively affordable because they have increased their housing supply (such as Alberta) will need to anticipate building even more housing if households continue to leave Canada’s expensive cities, if no action is taken to increase housing supply in those cities.
• Since households are now created because of changes in the housing system, the number of households relative to the size of the population changes by scenario. Lower house prices nationally will lead to more households relative to the size of the population in Canada. In particular, there will be more young households.
• The number of housing units to be built depends on local contexts that are constantly changing. More active monitoring of local population and economic conditions would be required.

Over the long term, housing affordability is driven by demand and supply. Economy-wide demand for housing grows with population and the size of the economy. In this section, we explore a scenario of how Canada might look in 2035 if it were to continue its current trend of homebuilding.

The Canadian population might reach nearly 45 million by 2035 compared to just over 41 million today (Figure 4 and Figure 5). This projection reflects data from Statistics Canada and includes policy changes to reduce immigration announced in 2024.^[1] The economy will be more than a fifth larger in real terms (Figure 6 and Figure 7). A larger economy relative to the size of the population improves affordability by our metric. This is because higher average incomes enable households to afford more housing if there’s enough supply.

Figure 4: Projected Population, Business-as-Usual, 2024 and 2035 (Millions)

Source: CMHC calculations.

Figure 5: Canada, Projected Population, Business-as-Usual, 2024 and 2035 (Millions)

Source: CMHC calculations. 

Figure 6: Projected Gross Domestic Product (GDP), Billions of Chained (2017) Dollars, Business-as-Usual, 2024 and 2035

Source: CMHC calculations. GDP in billions of chained (2017) dollars.  

Figure 7: Canada, Projected GDP, Billions of Chained (2017) Dollars, Business-as-Usual, 2024 and 2035

Source: CMHC calculations. GDP in billions of chained (2017) dollars.

We project that the annual rate of housing starts will be around 250,000 units by 2035. Therefore, the housing stock will increase by about 3 million units to reach close to 20 million units (Figure 8 and Figure 9). There will be significant growth in the housing stock in Alberta, for example. These projections reflect long-term trends, excluding the impact of any recent policy announcements.

Figure 8: Housing Stock in 2024 and 2035 (Business-as-Usual Scenario)

Source: CMHC calculations.

Figure 9: Canada — Housing Stock in 2024 and 2035 (Business-as-Usual Scenario)

Source: CMHC calculations.

These projections for the economy, population and supply imply a path for house prices and average incomes that together determine affordability. Figure 10 and Figure 11 shows that house prices will continue to increase and hurt affordability if there is no action to increase supply. Canadians moving from expensive regions will lead to proportionately greater price increases in regions such as Prince Edward Island and Saskatchewan, for example. Without additional supply, we would expect average rents to increase by about 40%, from around $1,400 today to over $1,900 by 2035.

Figure 10: House Prices ($), Q3 2024 and Q4 2035

Source: CMHC calculations.

Note: House prices ($) represent the average price of a fixed basket of residential properties with changes in value based on a CMHC repeat sales price index. This is a different price measure than forecasted in the CMHC Housing Market Outlook (HMO) publication.

Figure 11: Change in House Prices (%) Between Q3 2024 and Q4 2035 (Business-as-Usual Scenario)

Source: CMHC calculations.

Note: House prices ($) represent the average price of a fixed basket of residential properties with changes in value based on a CMHC repeat sales price index. This is a different price measure than forecasted in the CMHC Housing Market Outlook (HMO) publication.

[1] While the composition of the population reflects the Statistics Canada M1 scenario, the level of population is developed by CMHC. CMHC uses population projections to generate projections of household numbers within our modelling.

As the size of the economy and the population grow, demand for housing increases. Without a proportional increase in housing supply, affordability will suffer. In our modelling structure, we ask how much housing supply should be built to return to housing affordability over the next decade.

How much housing is required?

We estimate that housing starts averaging around 480,000 units annually over the next decade is required, compared to the 245,000 in our current projection (Figure 12 and Figure 13). The rate of increase required varies across the country. Notable increases required in areas such as Ontario outside of Toronto, as well as Montréal and Nova Scotia. This reflects the sharp loss of affordability since the pandemic.

In some areas of Canada, such as Edmonton, no additional supply of market housing is required, since these are projected to build sufficient housing to maintain affordability over the next decade. In many of these areas there remain housing challenges such as homelessness.

Figure 12: Projected Annual Housing Starts, 2025 to 2035

Source: CMHC calculations.

Figure 13: Canada, Projected Annual Housing Starts, 2025 to 2035

Source: CMHC calculations.

What will be the impact of increasing housing supply?

Household numbers will increase

As a result of lower prices, more households will be created. As younger adult Canadians are able to leave the family home, there will be a notable increase in the number of households among younger age cohorts (as well as some increase in other age brackets). Overall, reducing the cost of housing will increase the number of households by roughly 2% in 2035 compared to where it would be otherwise.

Population flows will increase

Changing patterns of housing supply and improved affordability across the country will create flows of households taking advantage of lower housing costs. A greater supply of housing outside of Toronto to restore lost affordability will lead to some households leaving Toronto for the rest of Ontario.

A similar pattern will take hold in British Columbia (Figure 14). In Quebec, more households will move to Montréal because there will be more housing in Montréal to restore the affordability lost since 2019. There’s less change in Alberta because there was less change in prices and rents from the pre-pandemic period.

Figure 14: Difference in Population Between "Additional-Supply" and Business-as-Usual Scenarios, 2035

Source: CMHC calculations.

Price changes

Returning to 2019 affordability levels in the next decade would lead to house prices being roughly a quarter lower than where they would otherwise be in 2035. Average rents would be lower by about 5%.

Figure 15 and Figure 16 show that increased supply would lead to price declines relative to today in some areas such as Nova Scotia. However, these areas experienced a sharp price increase since the pandemic. Other areas will see price growth because they’re relatively affordable today. As a result, we haven’t set tight affordability goals for them. Increases in supply will keep price growth in check in Toronto and Vancouver.

While there are concerns that increasing housing supply would cause house prices to fall rapidly and pose a risk to financial stability, this is unlikely. Housing supply cannot be increased rapidly enough in reality to trigger such an event.

In fact, the impact of increasing housing supply across the country will be much more nuanced in practice. New housing is expensive because of construction costs and better-quality finishing. Over time, through the process of filtering, more supply puts downward pressure on house prices.

Increasing housing supply is unlikely to cause financial instability because these forces take time to produce reactions. The slow pace of change in housing is why we’ve moved to a rolling 10-year horizon for our results.

Figure 15: House Prices ($), Q3 2024 and Q4 2035

Source: CMHC calculations.

Note: House prices ($) represent the average price of a fixed basket of residential properties with changes in value based on a CMHC repeat sales price index. This is a different price measure than forecasted in the CMHC Housing Market Outlook (HMO) publication.

Figure 16: Change in House Prices (%) Between Q3 2024 and Q4 2035 ("Additional-Supply" Scenario)

Source: CMHC calculations.

Note: House prices ($) represent the average price of a fixed basket of residential properties with changes in value based on a CMHC repeat sales price index. This is a different price measure than forecasted in the CMHC Housing Market Outlook (HMO) publication.

Rental and ownership

Our model projects the future path of average rents separately from the path of house prices. Both of these respond to changes in supply and demand and to each other. Their paths can diverge because they react differently to interest rates, for example. Increasing housing supply to lower the price of homeownership will lead to some renters moving from rental to homeownership.

Figure 17 shows the impact of increasing housing supply on average rents across Canada. We do not currently target a specific level of affordability for households in rental units.

Figure 18 shows a breakdown of additional supply, given the changing patterns of rents and house prices and the rise in ownership rates.

Figure 17: Difference in Rents Between "Additional-Supply" and Business-as-Usual Scenarios, 2035 (%)

Source: CMHC calculations. Average rent of purpose-built private rental units (apartments and rows, all bedroom types). This is a different rent measure than forecasted in the CMHC Housing Market Outlook (HMO) publication.

Figure 18: Projected Share of Total Additional Annual Housing Starts (Beyond Business-as-Usual), 2025 to 2035, by Tenure (%)

Source: CMHC calculations.

All models are, by necessity, simplifications of reality. There are many real-world features that are omitted because, for example, we don’t have the appropriate data or an understanding of all potential interactions. In this section, we outline how results might change under different approaches, leaving aside “normal” uncertainties of projecting the future.

The complexity of our model is significantly greater than our previous effort. So, we also explore how sensitive the analysis is to different circumstances. Scenario analysis is important, particularly in a world where demand for housing can change rapidly but the supply system does not.

Demographic-only and economic approaches to understanding affordability and housing supply

The traditional approach adopted by planners is to:

• take demographic projections of population growth from agencies such as Statistics Canada
• transform them into projections of household numbers (as CMHC does)
• use these household projections to assess how much housing is needed

The housing required reflects the growth in the number of households.

Added to this number will be the additional housing required to address suppressed household formation; that is how many additional households there would have been if house prices hadn’t been so high. This is done by using a past reference point of household numbers when housing was more affordable.

This approach has many advantages and is widely adopted and implemented across Canada. The data exists to support it, particularly at the local or municipal level. But it does have shortcomings, as it doesn’t include:

1. explicit affordability targets; or
2. demand for more housing increasing from economic variables such as higher incomes and falling housing costs

These are addressed in our economic modelling. The economic approach incorporates the demographic approach by including detailed population and household projections. It then adds in the impact of economic variables such as incomes and interest rates. The supply requirements projected by an economic model will meet a defined affordability target.

The downside to the economic approach is that it’s significantly more complicated and difficult to apply at the local level.

Incorporating additional effects in economic modelling explains why estimates of housing supply requirements are higher with economic modelling than with demographic-only modelling.

To illustrate this effect, consider the effect of building more housing. In the demographic approach this will lead to more households being created as, for example, adult children leave the family home. But more supply will also lead to lower average prices, and the demographic approach is silent on the impact of this effect.

Economic and statistical analysis finds that lower house prices lead to additional actions, such as:

• existing homeowners or renters moving to better-quality homes
• renters moving to homeownership, the purchase of second homes, and so on

As a result, even more housing needs to be built.

The magnitude of this effect is important. If it’s too large in our modelling, then the responsiveness of existing homeowners and renters to lower prices would be lower in reality and less housing would need to be built. To examine this, we can artificially lower this responsiveness in our modelling.^[2]

Reducing the responsiveness to its lowest plausible level reduces the number of additional housing starts required by 20% (Figure 19 and Figure 20). While this is a large difference in absolute terms, the underlying theme of the need for more housing supply remains intact.

Figure 19: Impact of Reducing Price Responsiveness: Projected Additional Annual Housing Starts (Beyond Business-as-Usual), 2025 to 2035

Source: CMHC calculations.

*Reducing the responsiveness to prices to the minimum value we can expect with 95% confidence.

Figure 20: Canada — Impact of Reducing Price Responsiveness: Projected Additional Annual Housing Starts (Beyond Business-as-Usual), 2025 to 2035

Source: CMHC calculations.

*Reducing the responsiveness to prices to the minimum value we can expect with 95% confidence.

We need to do further work in this area. Although we show results by different types of housing (rental versus homeownership), we need to incorporate more explicitly how the demand for particular types of housing increases as incomes rise or as housing costs fall. It’s possible that reflecting the differences across housing types would reduce the number of homes that need to be built, since it would be easier to match what households would like to live in with housing that’s available.

How might households respond to credible plans to increase housing supply, and might they move to other means of saving?

While it’s possible to see housing as only a means of shelter, Canadians tend to increase expenditure on housing as their incomes rise. They may want better housing with more surface area or in better locations, or see it as a means of savings and a way to benefit from higher prices.

What might happen if housing supply were to increase meaningfully over time at the scale this report suggests? First, this would be a gradual process over many years. Builders and developers can’t hire the workers and ramp up investment quickly. Approval processes take time.

Some critics of previous supply gap reports suggested that an overnight increase in housing supply of the magnitude suggested in the reports would lead to sharp price decreases for housing that would drive a spike in debt defaults. This doesn’t mesh with the reality of the time it takes for construction to take place.

Indeed, a critical argument for increasing housing supply and restoring affordability is to prevent rapid adjustment being forced on us. A global economic downturn that leads to widespread unemployment and mortgage defaults would be such an event. Canada’s high level of household indebtedness creates this vulnerability.

As households see realistic policy commitments that increase housing supply, they will likely lower the amount of their income devoted to housing over time. This would also mean less housing that needs to be built.

We can explore these effects in our modelling. Now, higher incomes create more demand for housing, but we can lower the extent to which this happens to its lowest plausible level based on our statistical analysis.^[3] In this experiment, the amount of additional housing starts required is reduced by 14%. If there were a change in Canadians’ interest in the housing market, then less additional supply would be needed over the long term to restore affordability.

Figure 21: Impact of Reducing Income Responsiveness: Projected Additional Annual Housing Starts (Beyond Business-as-Usual), 2025 to 2035

Source: CMHC calculations.

*Reducing the responsiveness to income to the minimum value we can expect with 95% confidence.

Figure 22: Canada — Impact of Reducing Income Responsiveness: Projected Additional Annual Housing Starts (Beyond Business-as-Usual), 2025 to 2035

Source: CMHC calculations.

*Reducing the responsiveness to income to the minimum value we can expect with 95% confidence.

[2] Technically, we reduce the responsiveness to lower prices to the minimum value we can expect with 95% confidence.

[3] We lower the income elasticity of demand to the minimum level we can expect with 95% confidence.

The modelling infrastructure developed here can be adapted to look at a variety of scenarios. A broader range of economic and demographic scenarios will be developed over time to consider alternative outcomes for the housing system. To illustrate potential uses, we look at the impact of improving productivity in the construction industry.

We think of productivity in this case as the output per worker. More output per worker can come about through increasing skills, automation, mass manufacturing, the digitization of housing planning, stronger supply chains and so forth.

Using more technology would allow construction to occur faster or with fewer mistakes. Offsite mass manufacturing of large components of housing and their assembly on site could enable more homebuilding with the same number of workers.

We introduce this idea into our modelling as reductions in the cost of labour per dwelling. There are real-world benefits that we can't capture, such as faster completion times. Unfortunately, in this type of modelling, we also can't capture why these changes may come about.

To illustrate the potential benefits of improving productivity in the construction industry, we look at the impacts of:

1. a 10% increase in productivity; and
2. a 31% increase in productivity to match the average level of productivity across all industries

These productivity improvements from the current workforce would add significantly to the housing stock and reduce house prices by 2% to 6% (Figure 23, Figure 24 and Figure 25).

In turn, increases in productivity that lead to lower prices in 2035 will have a slightly dampening effect on the incentive to build more housing, which is reflected in modelling results.

Figure 23: Canada — Impacts of Improving Productivity in Construction: Difference in the Housing Stock Between the Productivity Shocks And Business-as-Usual, 2035 (%)

Source: CMHC calculations.

Figure 24: Canada — Impacts of Improving Productivity in Construction: Average Annual Additional Housing Starts (Beyond Business-as-Usual) from 2025 to 2035 (Units)

Source: CMHC calculations.

Figure 25: Canada — Impacts of Improving Productivity in Construction: Difference in House Prices Between the Productivity Shocks And Business-as-Usual, 2035 (%)

Source: CMHC calculations.

The need to increase productivity in construction is evident not only from the intense need to produce more housing but also from the relatively slow rate of growth in productivity in this industry.

Evidence from the United States, which we're now refining for the Canadian context, suggests that the pace of productivity growth in construction has been low. The reasons for this are complex but American evidence points to the relatively heavy local regulatory burden placed on the industry. Many firms are too small to make the investments in technology needed to increase productivity.

The need to improve productivity in residential construction is also important given the broader implications of the need to increase supply. Increasing housing supply will mean that the residential construction industry must get bigger, taking more investment and workers, but this means taking resources from the rest of the economy.

This need poses a risk that could damage the long-term prospects of the Canadian economy if the productivity of the industry remains low.