Overview

This note contains the Bank of Canada’s 2024 staff assessment of potential output in Canada. Between 2023 and 2027, potential output growth is expected to average around 2% annually. Relative to the April 2023 assessment (Champagne, Hajzler et al. 2023), the level of potential output is revised up in the near term but is roughly unchanged by 2026 (Table 1).

This upward revision mostly reflects higher-than-expected population growth, underpinned by a surge in newcomers to Canada since the second half of 2022. Potential output growth in 2023 is relatively unchanged because the higher-than-anticipated contribution from population growth was offset by lower trend labour productivity. Over 2024–26, investment and trend total factor productivity (TFP) are expected to be lower. Population growth is also expected to be lower in 2025 and 2026, reflecting the federal government’s recently announced plans to reduce arrivals of non-permanent residents. We consider both upside and downside risk scenarios and construct a range around our benchmark estimates, with a focus on the uncertainty around population growth and business investment.

Table 1: Comparison of potential output estimates relative to April 2023

Table 1: Comparison of potential output estimates relative to April 2023 Annual rates (%)
  Potential output Revisions to the level of potential output
Annual growth Range for growth
2023 2.3 (2.3) (1.4–3.2) 0.8
2024 2.5 (2.1) 2.1–2.8 1.2
2025 1.7 (2.1) 1.1–2.4 0.8
2026 1.5 (2.2) 0.9–2.2 0.1
2027 1.7 1.1–2.4 ——

Note: Estimates from the April 2023 assessment appear in parentheses. The range for potential output growth represents the methodological range implied by the risk scenarios presented in Table 2.

Revisions to potential output

Compared with the April 2023 assessment, potential output is 0.8% higher in 2023 and 1.2% higher in 2024 (Table 1, column 3). The positive revisions mostly reflect larger-than-expected increases in the size of the working-age population, underpinned by a surge in newcomers to Canada, which are contributing to trend labour input (TLI). Statistics Canada revisions to historical gross domestic product (GDP) data also contribute to the higher estimates for potential output in 2023, although to a lesser extent.

Revisions over history

The unanticipated increase in population is the key driver of our revision to potential output relative to the April 2023 assessment. In 2023, Canada experienced a record number of flows of permanent residents and non-permanent residents, including holders of both temporary work and study permits. These contributed significantly to increases in the working-age population.1 Non-permanent residents accounted for most of these new arrivals. At over 800,000, net inflows of non-permanent residents in 2023 far outpaced 2022 flows and exceeded expectations in the 2023 assessment. The Canadian population at the end of 2023 was about 2.3% higher than anticipated at the time of the 2023 assessment.2

Increases in the overall population, and specifically in the number of working-age people, directly impact TLI. In addition, newcomers have employment rates that are generally higher than the overall average (Champagne, Ens et al. 2023). At the same time, the increase in TLI reduces capital per worker, weighing on labour productivity. Businesses will be incentivized to invest in new machinery and equipment to match the now larger labour force and to meet the rise in aggregate demand, but it will take time for the capital stock to catch up with the increase in labour. The net impact of the population revisions in 2023 is a 1.7% increase in TLI growth that is partially offset by a 1.3% decrease in trend labour productivity. This amounts to an increase in potential output growth of 0.4 percentage points (pps) in 2023 (Chart 1).

Changes to potential output since the previous year’s assessment also capture new data published by Statistics Canada:

  • The national accounts updates include historical revisions to GDP and investment.
  • The main update from the stock and flows data is the 2022 estimate of aggregate capital stock.

Together, these updates have impacted estimated historical TFP and trend TFP growth, increasing potential growth in 2021–22 but lowering growth in 2023 (Chart 1, green bars).3 Finally, in our cohort-based model, data updates related to the labour market have had little impact on the estimated growth of TLI or potential output.4

Chart 1: Potential output growth is revised up in 2024 and down in 2025–26, largely due to expected changes in population growth dynamics

Revisions over the projection

Over the projection, the size of the population is expected to be larger than anticipated at the time of last year’s assessment. This is the main driver of upward revisions to potential output in 2024. However, population growth is expected to slow because of the federal government’s recent commitment to reduce the share of non-permanent residents to 5% of the population in about three years. This reduces the contribution of population growth by the end of the projection, resulting in downward revisions to potential growth (Chart 1).

Labour productivity growth has been particularly weak since the onset of the COVID-19 pandemic, and this weakness is expected to persist for longer than previously anticipated. Weaker productivity growth over the projection reflects both slower-than-expected capital deepening and weak TFP growth.

While weak TFP growth is partly explained by temporary factors lingering after the economic recovery from the pandemic, evidence suggests that longer-term structural factors are also at play. We developed a bottom-up sectoral approach to better understand the sources of growth in the business sector (Box 1). Using this analysis to understand the recent underperformance of aggregate TFP growth and project it forward, we lowered the long-run trend TFP assumption (Chart 1, red bars). This change decreases potential output growth by about 0.2 pps, on average, over 2024–26.

Dynamics of potential output growth

After its sharp decline during the pandemic, potential output growth averaged slightly above 2% in 2021–22. Growth strengthened in 2023 and is expected to remain strong in 2024 before gradually decreasing over the projection. The strong growth in 2023 and 2024 is a result of strong TLI growth, which is expected to slow down through 2027 (Chart 2, blue bars).5 These dynamics are driven almost entirely by changes in the population due to immigration and the recently announced target for non-permanent residents for 2027.

Chart 2: Potential output growth decreases over the projection horizon

Trend labour productivity

Trend labour productivity growth is negative in 2023. It is expected to remain negative in 2024 as strong population growth continues to increase TLI and lower capital per unit of TLI (Chart 2, yellow bars). The rebound in 2025 is driven by capital deepening due to a pickup in business investment combined with a slowdown in population growth.6 Trend TFP growth remains relatively stable at around 0.5% annually during this period. Box 1 provides further analysis of the drivers of TFP, which is also an important driver for trend labour productivity.

Box 1: Total factor productivity

Box 1: Total factor productivity

Written by Dany Brouillette and Tessa Devakos

Total factor productivity (TFP) is an important driver of labour productivity but is hard to predict. In previous assessments of potential output, TFP growth was assumed to gradually converge to its historical, long-run average rate. In recent years, measured TFP growth has tended to fall below this historical average. This year, Bank of Canada staff developed a sectoral, bottom-up approach to better understand the sources of weakness in TFP growth in the business sector.7 The analysis also highlights the role played by structural factors such as digitalization, aging and climate change.8, 9

Aggregate TFP growth is projected to be lower in the current decade relative to its historical average by roughly 0.1 percentage point (Chart 1-A). Manufacturing, mining, and oil and gas are expected to be the main drivers of the weaker performance, while services should provide an offset. TFP growth in the manufacturing sector is expected to slow, driven by lower growth in durable goods. This is because the durable goods sector is projected to be less productive relative to the early 2010s when it strongly rebounded after the 2008–09 global financial crisis. TFP in the oil and gas sector is anticipated to start contracting again after a brief rebound in the late 2010s.10

Chart 1-A: Total factor productivity growth is expected to decline

Turning to the contribution of structural factors:

  • Digitalization (investment in computers and software) is expected to continue supporting TFP growth in the medium term following the boost from the pandemic (Chart 1-B).11
  • Aging is not expected to weigh down TFP growth as much going forward. This reflects the anticipated decline in the shares of young and older workers, two groups that are typically relatively less productive than prime-age workers.12
  • The influx of newcomers also contributes to positively offset the effects of aging because newcomers tend to be younger than the current Canadian population.
  • The impacts of climate change policies, captured through reallocation of resources across sectors, are positive but very small because these policies were implemented only in recent years.13

Chart 1-B: Structural factors have a substantial impact on total factor productivity

Trend labour input

TLI growth is expected to add 3.0 pps to potential output growth in 2024 before decreasing to an average contribution of 0.7 pps between 2025 and 2027. This mainly reflects the unusually high flows of newcomers, as discussed in the previous section. The recent increase in arrivals of non-permanent residents has helped to offset the long-run trends of population aging and declining trend employment rates that weigh on TLI.

We assume that population growth will remain strong in 2024 before declining through 2027 (Chart 3). Population growth is a key contributor to TLI. It added 3.1 pps to TLI growth in 2023 and is projected to contribute the same amount in 2024. The contribution of population growth is then expected to slow to 0.9 pps by 2027 as the new federal government immigration measures come into effect. Population gains remain the largest driver of TLI growth throughout the period.

The trend employment rate and trend average hours worked have smaller impacts on TLI growth. The contribution from the trend employment rate is expected to remain weak going forward. This reflects a broader trend that precedes the pandemic. Population aging, which is associated with declining participation rates in the labour force, has contributed to a gradual decline in the trend employment rate and trend average hours worked.

Chart 3: Population changes are driving growth in trend labour input

Uncertainty around the base-case scenario

Many of the components of potential output are not directly observable and are challenging to forecast. This creates uncertainty around the outlook. We discuss the main risks to the outlook in this section.

Population growth

Recent population growth has been driven mainly by flows of non-permanent residents, but these flows are difficult to predict. In March 2024, the federal government announced its first-ever target for the share of non-permanent residents in the total population, with the goal of reaching this target within the next three years.

The cumulative impact of the new target on population growth over the next three years is relatively clear. While net outflows of non-permanent residents will be required to meet this target, the timing of these outflows is uncertain. Specifically, population growth could vary substantially between years based on whether the required adjustments to flows of non-permanent residents are front-loaded or delayed. Moreover, the federal government publishes a target range for new permanent residents as part of its Immigration Levels Plan (between around 30,000 and 50,000 above or below the target). The baseline population growth projections assume the target immigration levels, and the bounds of the risk incorporate the government’s target range.

Therefore, in addition to our base-case scenario, we consider high and low population growth scenarios to present upside and downside risks to our potential outlook for 2024 to 2027:

  • The high-growth scenario assumes population increases that are 1.0 pps higher per year.
  • The low-growth scenario assumes population increases that are 0.4 pps lower per year.

The larger magnitude in the high-growth scenario reflects the large number of pathways for new non-permanent residents through Canada’s International Mobility Program that may be difficult to restrict in the near term. These pathways include those available to asylum seekers and spouses of skilled workers. Over the projection, these scenarios mainly reflect differences in assumptions about the evolution of net flows of non-permanent residents. The risk that flows of permanent residents fall short or exceed annual targets also matters, but to a lesser extent.

Compared with the baseline:

  • The high-growth scenario increases potential output growth by 0.2 to 0.5 pps over 2024–26 (Table 2).
  • The low-growth scenario lowers potential output growth by 0.1 to 0.2 pps over 2024–26.

Table 2: Comparison of risks to potential output

Table 2: Comparison of risks to potential output Change in annual rates (%)
Risk Scenario 2024 2025 2026 2027
Population growth lower -0.1 -0.2 -0.2 -0.2
higher 0.2 0.5 0.5 0.5
Investment growth lower -0.1 -0.1 -0.1 -0.1
higher 0.1 0.2 0.2 0.2
Total factor productivity growth lower -0.2 -0.3 -0.3 -0.3
Growth impact range   -0.4–0.3 -0.6–0.7 -0.6–0.7 -0.6–0.7

Box 2 provides further analysis of the impacts on the labour market from the high number of non-permanent residents.

Box 2: Immigration and real wages

Box 2: Immigration and real wages

Written by Julien Champagne, Mallory Long and Antoine Poulin-Moore

Between October 2022 and October 2023, Canada’s population grew at the fastest rate in 65 years, expanding by 3.2%, or about 1.3 million individuals. This was driven by a surge in international migration (Chart 2-A).

Meanwhile, the composition of immigrants coming to Canada has changed considerably since 2015. Historically, growth of the immigrant population in Canada came mostly from permanent residents.14 Non-permanent residents were mostly temporary foreign workers with short-term work permits; thus, their contribution to population growth was negligible. This relatively stable composition started to shift in 2015, coinciding with the introduction of the International Mobility Program. By 2019, about one-third of the immigrant contribution to annual population growth came from non-permanent residents. This proportion has recently doubled, and non-permanent residents accounted for two-thirds of the immigrant contribution to population growth as of October 2023.

Chart 2-A: Non-permanent residents have driven Canada’s population growth

Using data from the Labour Force Survey, we investigate how these flows are changing the demographic characteristics of the immigrant population.15 We also consider what employment patterns by industry and relative earnings of new immigrants could imply for labour productivity.16

The first striking pattern is the decline over the past four years in the share of employed non-permanent residents working in skilled occupations, as defined by the National Occupational Classification (Table 2-A).17 The average age of employed non-permanent residents has also decreased over this period. In contrast, the evolution of these characteristics was generally more stable or even positive for permanent residents (Table 2-A, first two rows).

The deterioration in the average skill level of non-permanent residents also coincides with lower average wages. The last column of Table 2-A shows real hourly wages of Canadian-born workers, non-permanent residents, and permanent residents who arrived in Canada less than and more than 10 years ago for 2019 and 2023. While the wages of the earlier immigrants are closer to those of Canadian-born workers and have been increasing over time, those of non-permanent residents are much lower and have fallen over this period. Because real hourly wages are typically correlated with labour productivity, this piece of evidence is consistent with non-permanent residents working in less productive occupations.

Table 2-A: Demographic characteristics of the immigrant population have shifted recently

Table 2-A: Demographic characteristics of the immigrant population have shifted recently
Year Age Skills Real wage
2019 2023 2019 2023 2019 2023
Permanent residents (1–10 years) 36.6 35.9 62.9% 68.8% $19.61 $21.42
Permanent residents 11+ years 47.2 47.6 70.2% 73.5% $23.22 $24.14
Canadian-born workers 41.0 41.1 69.5% 72.1% $23.74 $24.43
Non-permanent residents 34.0 32.7 62.7% 61.7% $19.97 $19.09

Note: This table displays averages of labour market characteristics of employed people by year and immigration group based on microdata from the Labour Force Survey. Permanent residents (1–10 years) includes permanent residents who arrived in Canada in the past 10 years. Permanent residents 11+ years includes permanent residents who arrived more than 10 years ago. The real wage measure reflects hourly nominal wage computed as average weekly earnings divided by actual weekly hours worked, deflated by the consumer price index. The skills variable represents the share of skilled employment based on the National Occupational Classification.

This finding is also corroborated by looking at the allocation of non-permanent residents across sectors. While the increase in their shares has been broad-based, it has also been disproportionately large for some of the lower-productivity industries such as accommodation and food services; retail trade; and business, building and other support services (Chart 2-B).

Chart 2-B: Sectoral reallocation of immigrant labour has been important

Investment growth

The outlook for investment growth in Canada is uncertain. On the upside, there is a potential for greater business investment. The large increase in the labour force, including the working-age population, supported by the exceptional flows of non-permanent residents, presents businesses with new opportunities to increase investments in capital to make better use of this new workforce. And there are recent investment incentives to support the transition to a green economy. In addition, governments’ willingness to match green incentives available in other countries could lure additional investment to the green transition (Box 3).

On the downside, deglobalization and disruptions to global trade remain ongoing concerns. The uncertainty caused by such events can limit business investment. Overall risks surrounding these events are in line with last year’s assessment of potential output (Champagne, Hajzler et al. 2023). Uncertainty related to the design and implementation of climate policies may also negatively impact business investment in the medium term (Box 3).

We estimate that the risks to investment are broadly symmetrical, with an impact on potential output of between 0.1 and 0.2 pps annually (Table 2).

Box 3: Climate transition and investment

Box 3: Climate transition and investment

Written by Craig Johnston, Raven Wheesk, and Tatjana Dahlhaus

The transition to a low-carbon economy is an important driver of structural change across sectors, forcing businesses to reassess the transition impact on any investment. However, predicting the overall impact on business investment is challenging because of the many competing channels. Below, we provide a qualitative discussion of the main drivers at play.

Policy

Climate policies can impact the cost of capital and profitability, influencing investment decisions in distinct ways across sectors. For example:

  • Carbon pricing increases the cost of carbon-intensive activities—thus incentivizing businesses to invest in cleaner technologies and practices to reduce emissions—and discourages investment in hard-to-abate, emissions-intensive sectors.18
  • Clean energy investment tax credits make investing in low-carbon sectors and technologies more economically attractive than alternative sectors.19 Additionally, the willingness of governments to match incentives available in other countries may prevent some green investment from leaving Canada.20
  • Cap-and-trade systems set emissions limits and allocate tradable permits to entities. While this increases costs for emissions-intensive firms, discouraging investment because of reduced profitability, it also prompts investment in emissions reduction measures to avoid purchasing additional permits.

Uncertainty

Uncertainty can dampen business investment by creating hesitancy and caution among companies (Bloom 2009; Bloom et al. 2018; Baker, Bloom and Davis 2016; Alexopoulos and Cohen 2015). This channel could be enhanced by the long time it can take to build many green projects and the dependence of these projects on climate policies to make them viable. Key sources of uncertainty related to decarbonization include:

  • Policy and regulatory uncertainty. Uncertainty over the design and implementation of climate policies may be rising over time (Lin and Hengsong 2023), deterring investment due to the unpredictability of future returns. In addition, political and regulatory barriers are difficult to predict and may discourage investment in and deployment of future projects (Karatayev et al. 2016; Nasirov, Silva and Agostini 2015; Seetharaman et al. 2019).
  • Technology uncertainty. The continued development of emerging low-carbon technologies including carbon capture, utilization, storage and hydrogen, for example, could support continued production and investment in emissions-intensive sectors.
  • Critical inputs and geopolitical uncertainty. The degree to which supply and supply chains for the critical minerals and raw materials necessary for the transition to a low-carbon economy are secure may influence investment decisions. Among the key challenges are the expected increase in demand for certain metals essential for meeting climate goals21 and the concentration of the supply of many key minerals in a limited number of regions.22
    • On the one hand, the uncertain supply and the vulnerability of supply chains for critical minerals create risks of resource scarcity, and supply disruptions could hinder the development of and investment in low-carbon technologies.
    • On the other hand, efforts to insulate the energy transition from possible supply chain issues could spur further domestic investment.

Financing

The inability to mobilize sufficient financing poses a risk to investment. To meet climate objectives, a significant increase in investment may be required.23 However, investors may be deterred for various reasons, including potential greenwashing and concerns about the long-term financial viability of low-carbon projects.

  • Greenwashing—the misleading portrayal of a product, service or company as environmentally friendly—can deter climate investment by eroding investor trust and confidence in climate-oriented investments. However, the development of green taxonomies can help provide clarity for capital markets by defining financial investments or assets as supportive of climate objectives.
  • Investors’ decisions to funnel capital to low-carbon initiatives also hinge on expectations of future climate policies. Heightened uncertainty surrounding these policies could discourage the availability of capital for climate initiatives.

Total factor productivity growth

Growth in TFP is associated with technological change, organizational change or economies of scale. Business investment is often spent on modern technology that increases TFP (see, for example, Restuccia 2004). If the weakness in capital accumulation in Canada since the mid-2000s continues or even intensifies, this could also result in lower TFP growth than our base-case scenario (Gu 2024).

In addition, there is a risk that TFP growth could be impacted by initial productivity differences between newcomers and Canadian-born workers or more established immigrants. Recent data point to a widening wage gap between non-permanent residents and Canadian-born employees (Box 2). This gap is largest during the first years newcomers are in Canada, given that it takes time to adapt to the labour market in a new country and to reach one’s full potential in the labour market. To the extent that wages partially reflect the labour compensation component of TFP, the flows of non-permanent residents could weigh on TFP growth in the short term.24

We estimate that these two downside risks could decrease potential output by between 0.2 and 0.3 pps annually between 2024 and 2027 (Table 2).

Appendix

Table A-1: Comparison of Canadian potential output estimates relative to April 2023

Table A-1: Comparison of Canadian potential output estimates relative to April 2023 Annual rates (%)
  Annual growth Trend labour input growth Trend labour productivity growth Range for growth Revisions to the level (percent)
2023 2.3 (2.3) 2.9 (1.5) -0.6 (0.8) —— 0.8
2024 2.5 (2.1) 3.0 (1.3) -0.5 (0.8) 2.1–2.8 1.2
2025 1.7 (2.1) 0.9 (1.2) 0.8 (0.9) 1.1—2.4 0.8
2026 1.5 (2.2) 0.6 (1.2) 0.9 (1.0) 0.9—2.2 0.1
2027 1.7 0.6 1.0 1.1—2.4 ——

Note: Estimates from the April 2023 assessment appear in parentheses. Numbers may not add to total due to rounding. The range for potential output growth represents the methodological range implied by the risk scenarios.

References

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  1. 1. See Statistics Canada (2023).[←]
  2. 2. These population estimates are for people aged 15 years and older. The 2023 population growth estimate is based on a combination of data from Statistics Canada’s Labour Force Survey and quarterly population estimates.[←]
  3. 3. The positive revisions to historical GDP are associated with higher GDP growth in 2021–22 and more subdued growth in 2023, pushing estimated trend TFP growth in the same directions. The stock and flow update is associated with a relatively weak TFP estimate in 2022, which lowers trend TFP growth in both 2022 and 2023. On net, trend TFP growth is somewhat higher in 2022 and lower in 2023.[←]
  4. 4. See Barnett (2007) for a detailed description of the cohort-based model of TLI.[←]
  5. 5. For more details, see Table A-1 in the Appendix.[←]
  6. 6. Capital deepening is growth in aggregate capital stock per trend hour worked, the latter measured through TLI. It is therefore positively related to capital accumulation (i.e., fixed asset investment) and negatively related to TLI.[←]
  7. 7. See Brouillette, Devakos and Wheesk (forthcoming).[←]
  8. 8. We used a reduced-form regression of TFP on digital and aging indicators to estimate the impacts of digitalization and aging. To estimate the impacts of climate change policies, we used G-cubed, one of the general equilibrium climate change models used at the Bank. We then adjusted base-case sectoral TFP profiles to account for the estimated impacts of structural factors. Finally, we combined these profiles with sectoral shares (from G-cubed) to obtain aggregate TFP.[←]
  9. 9. G-cubed is a multi-sector, multi-country general equilibrium model that has been extended to assess the impacts of climate policy (see for instance McKibbin and Wilcoxen 2013).[←]
  10. 10. Gu and Willox (2023) and Haun and Sargent (2023) offer alternative sectoral decompositions of labour productivity by source of growth. They also compare productivity growth in Canada and the United States.[←]
  11. 11. See Mollins and Taskin (2023) for a more detailed discussion on the link between digitalization and productivity.[←]
  12. 12. See Guenette and Shao (forthcoming) for a global discussion of demographics and productivity.[←]
  13. 13. See Barr, Foltin and Tang (2023) for a discussion on digital and green transitions in Canada.[←]
  14. 14. Immigration, Refugees and Citizenship Canada defines a permanent resident as someone who has been given permanent resident status upon immigrating to Canada but is not a Canadian citizen. Non-permanent residents generally include asylum seekers and people with study or work permits.[←]
  15. 15. It is worth noting that the Labour Force Survey might not properly sample the population of non-permanent residents. Skuterud (2023) provides an overview of the potential biases.[←]
  16. 16. This research question will be investigated further in a forthcoming staff analytical note.[←]
  17. 17. There are six categories of training, education, experience and responsibility in the 2021 National Occupational Classification. The first four categories are classified as high-skilled occupations. For more details, see the Statistics Canada website.[←]
  18. 18. Some argue that oil and gas producers may seek to sell more oil today by front-loading investment and extraction before climate policies lead to demand destruction (Baur and Todorova 2023; Li, Trencher and Asuka 2022; Sinn 2012). The Bank of Canada’s survey intelligence suggests this is not currently happening in Canada.[←]
  19. 19. Since 2022, the Government of Canada has introduced investment tax credits for investments in clean technology, clean hydrogen production, carbon capture, clean technology manufacturing and clean electricity.[←]
  20. 20. For example, there are forgivable loans and production subsidies, as exemplified by the recently announced $7 billion Northvolt electric vehicle battery plant.[←]
  21. 21. For example, lithium demand will increase by 150% from 2022 to 2030, according to the most conservative scenario from the International Energy Agency. Under a scenario where net zero is achieved, lithium demand will rise by 450% by 2030.[←]
  22. 22. For example, cobalt is a critical battery mineral, yet over 70% of global cobalt reserves are found in the Democratic Republic of the Congo (US Geological Survey 2023).[←]
  23. 23. Some estimates suggest that Canada may require around $80 billion to $115 billion each year in new investments to achieve its climate targets (Arnold and Leech 2023; Sustainable Finance Action Council 2022).[←]
  24. 24. The labour compensation component of TFP is sometimes referred to as labour composition. It captures changes in aggregate productivity associated with changes in the average skills and human capital of the labour force.[←]

Acknowledgements

We acknowledge the contributions of Dany Brouillette, Julien Champagne, Tatjana Dahlhaus, Mallory Long, Youngmin Park, Kurt See and Raven Wheesk to the analysis presented in this note. We thank Marc-André Gosselin and Alexander Ueberfeldt for their comments and suggestions. We also thank Carole Hubbard and Jordan Press for their editorial assistance. Finally, we thank Denis Clairand and Philippe Audet-Cayer for their help in translating this note into French.

Disclaimer

Bank of Canada staff analytical notes are short articles that focus on topical issues relevant to the current economic and financial context, produced independently from the Bank’s Governing Council. This work may support or challenge prevailing policy orthodoxy. Therefore, the views expressed in this note are solely those of the authors and may differ from official Bank of Canada views. No responsibility for them should be attributed to the Bank.

Content Type(s): Staff research, Staff analytical notes
Topic(s): Economic models, Labour markets, Monetary policy, Potential output, Productivity
JEL Code(s): E, E2, E3, E4, E5

DOI: https://doi.org/10.34989/san-2024-11

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