## CHAPTER 3 SLOWDOWN IN gLObaL MEDIUM-TERM gROWTH: WHaT WILL IT TaKE TO TURN THE TIDE?

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### Overview and authorship
- Authors: Nan Li (co-lead), Chiara Maggi, Diaa Noureldin (co-lead), Cedric Okou, Alexandre B. Sollaci, and Robert Zymek, with support from Shrihari Ramachandra, Pablo Vega, Yarou Xu, and Dennis Zhao.
- External consultant: Peter Klenow.
- Support: Macroeconomic Policy in Low-Income Countries program of the UK’s Foreign, Commonwealth and Development Office (FCDO) and Macroeconomic Research on Climate Change and Emerging Risks in Asia program of the Ministry of Economy and Finance of the Government of Korea.
- Note: The views expressed do not necessarily represent the views of the supporting partners.

### Main findings
- The decline in medium-term growth projections is widespread and reflects secular forces rather than forecaster pessimism.
  - Expectations for medium-term growth have been revised downward across all income groups and regions, most significantly in emerging market economies.
- Total factor productivity (TFP) dynamics are a principal driver of the decline in actual growth.
  - In advanced economies, productivity growth began decreasing before the global financial crisis.
  - In emerging market and developing economies, TFP growth rose before the crisis and then fell, mirroring the globalization cycle.
  - Changes in TFP growth have accounted for more than half of the decline in advanced and emerging market economies and nearly all of the decline in low-income countries.
- Increased misallocation of capital and labor among firms has exerted a drag on TFP of 0.6 percentage point a year in the economies considered.
  - This implies TFP growth could have been 50 percent higher absent the rise in misallocation.
  - Two-thirds of measured misallocation at any time is attributable to persistent structural frictions; about one-third is transitory.
- Reduced private capital formation since the global financial crisis has contributed to the growth decline.
  - Deterioration in firms’ valuations relative to the cost of capital and rising corporate leverage are key firm-specific contributors to lower business investment.
- Demographic pressures are expected to intensify.
  - By 2030, global labor supply growth is projected to be 0.3 percent, less than a third of its average in the decade before the pandemic.
- Policy conclusion:
  - Returning global growth to the historical (2000–19) annual growth average of 3.8 percent requires growth-enhancing policies and reforms to improve allocative efficiency and labor participation, facilitate cross-border trade and knowledge exchange, enhance innovation capabilities, and maximize capacity to benefit from technological advances such as AI.
  - Without such policies and under conservative technological assumptions, global growth in the medium term could fall below 3 percent.

### Insights from medium-term forecasts
- Five-year-ahead WEO growth projections show a broad-based downturn in growth prospects since 2008 affecting nearly 82 percent of economies, including the world’s largest.
- The five largest emerging market economies—Brazil, China, India, Indonesia, and Russia—contributed approximately 0.8 percentage point of the 1.8 percentage point drop in projected global growth.
- The downshift is evident across regions and most pronounced for East Asia and the Pacific.
- Examination of forecast errors shows no evidence of a pessimism bias in forecasters’ five-year-ahead forecasts.
- WEO medium-term growth forecasts are generally aligned with potential output growth; deviations occur mainly after crises when faster growth is expected to close large output gaps.
- Catch-up (income convergence) explains only about a quarter of the projected global growth decline since 2008.
- Measures suggest the pace of convergence in income and social welfare is slowing or potentially reversing over the medium term.

### How did we get here? — Growth decomposition and TFP
- Global growth accelerated in the early 2000s until the 2008 global financial crisis and has declined since; per capita GDP growth followed a similar pattern with a modestly smaller postcrisis decline due to slower population growth.
- For all country groups, shifts in growth have been primarily the result of changes in TFP growth:
  - Advanced economies: annual TFP growth fell from 1.3 percent during 1995–2000 to 0.2 percent after the pandemic, accounting for half of the GDP growth reduction.
  - Emerging market economies: TFP growth dropped from 2.5 percent during 2001–07 to 0.7 percent after the pandemic.
  - Low-income countries: TFP growth fell from 2 percent during 2001–07 to nearly zero after the pandemic.
- Slower capital formation after 2008 for advanced economies and since 2013 for emerging market economies also contributed to the slowdown.
- A consistent decline in the labor contribution—driven by aging populations and retreating labor force participation in major economies—further suppressed growth.

### A demographic drag on labor supply
- Working-age population (ages 15–64) growth has slowed in about 92 percent of the global economy since 2008 and has been negative in about 44 percent.
- Several large economies (Canada, China, United Kingdom, United States) experienced the demographic turning point around the global financial crisis.
- Nearly two in every three new entrants to the global workforce over the medium term will come from India and sub-Saharan Africa.
- Shift-share analysis of labor force participation (2008–21):
  - Aggregate participation rates declined in most regions except Advanced Asia and the Pacific, the Middle East and North Africa, Europe, and Canada.
  - The drag from aging is visible in all advanced economies and China, and to a lesser extent in Latin America.
  - Advanced economies—except the United States—increased within-group labor force participation, largely via gains in female participation and higher participation of older workers.
  - Decline in male participation was a drag in emerging market economies and the United States.
- The pandemic exacerbated participation drops between 2019 and 2020; participation remained broadly lower than in 2019 in Latin America (about 1.9 percentage points) and the United States (about 1.4 percentage points).
- Policy associations with participation (OECD sample):
  - Reduced unemployment benefits and lower labor taxes are associated with higher participation for men aged 25 to 54.
  - Expansion in secondary education enrollment is associated with higher future participation for women aged 25 to 54.
  - Labor market programs and childcare programs support female participation.
  - Retirement-age reforms and spending on labor market programs are associated with higher participation for older workers (ages 55 to 64).

### Anemic private capital formation
- Business investment in OECD economies tumbled after 2008 and in 2021 fell by about 40 percent of its pre-global-financial-crisis trend.
- Instrumental-variable estimate: for every 1 percentage point decline in output growth that is not triggered by a contraction in business investment, there is a corresponding 2 percentage point decrease in investment growth.
- As of 2021, about half of the shortfall in business investment since 2008 can be linked to weaker economic activity (comparison with precrisis trend).
- Firm-level sample and measurement:
  - Publicly listed firms in 32 advanced economies and 13 emerging markets.
  - Net investment rate = investment divided by lagged capital stock net of depreciation; investment and capital stock figures account for intangibles.
- Aggregate investment-rate changes since 2008:
  - Overall investment rate declined, on average, by about 2.3 percentage points in advanced economies.
  - Overall investment rate declined by about 2 percentage points in emerging markets.
  - Regression analysis explains more than half of the decline in advanced economies and virtually all of the decline in emerging markets using included determinants.
- Key firm-level determinants since 2008:
  - Tobin’s q decreased by 10 to 30 percent on average, contributing the bulk of the explained decline in investment.
  - Emerging markets experienced a 20 percent average increase in leverage after 2008, materially contributing to the investment fall.
  - Investment rates increase with Tobin’s q, profits, and cash stock; decrease with higher corporate leverage and the cost of debt.
- Macro factors:
  - The decline in GDP growth since 2008 helps explain the investment decline even after controlling for firm-level determinants.
  - Rising uncertainty after 2008 makes a smaller but still significant contribution to the investment decline in advanced economies.
  - Increased capital inflows since 2008 have been positive for investment in emerging markets.

### Productivity trends and the role of resource misallocation
- TFP growth has slowed over the past two to three decades due to waning ICT gains, declining business dynamism, tighter credit conditions, and slower cross-border capital and trade expansion.
- Allocative efficiency declined during 2000–19 in most countries in a sample of 15 advanced and 5 emerging market economies, using methods pioneered by Hsieh and Klenow (2009) and refined by Bils, Klenow, and Ruane (2021).
  - The median country experienced an average annual drag on TFP growth of about 0.9 percentage point from declining allocative efficiency.
  - For the median advanced economy, the drag was 0.5 percentage point; the median advanced economy saw TFP growth of only 0.5 percent during 2000–19, implying increased misallocation may have halved its TFP growth.
  - The United States was an exception: improvements in allocative efficiency helped boost annual TFP growth by 0.8 percentage point over the period.
- Decomposition:
  - Changing sector shares in GDP contributed only about 30 percent of the annual drag on TFP; the remainder is attributable to within-sector developments.
  - Structural transformation toward services (which display more inefficiency than goods) can reduce overall allocative efficiency.
- Firm-level dispersion and dynamics:
  - Dispersion of firms’ real productivity rose significantly leading up to the global financial crisis and remains elevated.
  - Wider dispersion implies faster-growing firms should attract capital and labor, but frictions slow adjustment; recovery is slow (9–11 years to return halfway to long-term level after shocks).
- Cross-country variation and policy links:
  - Structural allocative efficiency rises with market entry and competition, trade openness, financial access, and labor market flexibility.
  - No systematic evidence that changes in structural policies during 2000–19 explain the observed decline in allocative efficiency for the sample as a whole.
  - Policy scenario: if countries with allocative efficiency below the United States reduced their gaps in structural policies by 15 percent over 10 years, medium-term TFP growth could be boosted by 0.7 percentage point.

### Baseline medium-term projections (to 2030)
- Projection approach:
  - Labor force participation forecasts use a cohort-based approach with United Nations demographic projections, assuming stable employment rates.
  - Capital growth merges WEO public investment forecasts with the chapter’s estimates of the medium-term private investment rate.
  - TFP growth projects sectoral allocative efficiency moving gradually toward its estimated long-term level and reaching its half-life in the medium term; efficient TFP growth (net of misallocation) follows historical trend.
- Labor supply and contribution to global GDP growth by 2030:
  - By 2030, the annual contribution of labor supply to global GDP growth is expected to decrease to 0.2 percentage point, only a quarter of its 2000–19 average contribution.
  - This reflects a projected 0.3 percent growth of potential labor supply in 2030.
  - Regional note: Low-income countries projected labor-supply growth in 2030 is 2.1 percent.
- Contributions to medium-term global growth (baseline):
  - Labor supply:
    - A sharp reduction in participation will cause labor supply to contract by 0.6 percent in China and by 0.5 percent in the EU.
  - Capital:
    - Capital’s contribution to growth is expected to be 1.7 percentage points, compared with the 2000–19 average contribution of 2.1 percentage points.
    - Public investment accounts for 30 percent of emerging market and developing economies’ overall capital.
  - Total Factor Productivity (TFP):
    - The TFP growth contribution is expected to decline to 0.9 percentage point by 2030, down from the 2000–19 average of 1.0 percentage point.
    - Net effect: a decline in the TFP growth rate by 0.1 percentage point from its two-decade average prior to the pandemic.
  - Aggregate baseline projection:
    - World’s growth rate projected at 2.8 percent in 2030 under the baseline scenario.
    - Historical (2000–19) annual average growth was 3.8 percent.

### Alternative scenarios (impacts relative to baseline)
- Overall range:
  - Medium-term growth effects range from 1.2 percentage points above to 0.8 percentage point below the baseline.
  - Larger effects possible if scenarios occur simultaneously.
- Specific scenarios and impacts:
  - Policies to increase labor force participation:
    - Assumes countries increase participation rates by 3.2 percentage points (median increment if all countries converged to best policies).
    - Could increase labor supply growth by about 0.3 percentage point, contributing 16 basis points to global growth.
  - Migration boost to advanced economies’ labor supply:
    - Assumes an increase in labor supply equivalent to 1 percent of advanced economies’ projected labor force in 2030.
    - Could add 20 basis points to global growth.
  - Structural reforms reducing misallocation:
    - Assumes countries close 15 percent of their policy gap with the United States over the medium term.
    - Expected to enhance TFP growth by 0.7 percentage point and add 1.2 percentage points to global growth.
  - Improved talent allocation in emerging market and developing economies:
    - If talent allocations follow the United States’ trend, global growth could be boosted by 0.25 percentage point.
  - AI adoption:
    - Estimated global growth impact varies from 10 to 80 basis points in the medium term, depending on adoption and whether AI replaces or augments workers.
  - Legacy of high public debt:
    - Persistent elevated public debt could reduce medium-term growth by an estimated 5 to 15 basis points.
  - Geoeconomic fragmentation:
    - Limited “friend-shoring” scenarios could reduce growth by 10 basis points.
    - A more extensive reshoring scenario could lower medium-term growth by 80 basis points.
    - Larger losses could arise from reduced trade-associated knowledge spillovers and productivity loss not captured in the simulation.

### Key findings and risks
- Declining TFP, driven by increased resource misallocation and slower efficient TFP growth, is a central driver of the slowdown.
- Shrinking working-age populations in major economies and lackluster business investment also contribute to weaker medium-term growth.
- Without timely policy interventions and technological gains (notably from AI), global growth is likely to remain well below its prepandemic historical average in the medium term.
- Between-country convergence:
  - Cross-country convergence took place during 2008–19 and was fastest during 2008–12; the rate turned positive after the pandemic.
  - Current projections point to no convergence over the medium term.
- Global inequality:
  - Although inequality decreased since the mid-2000s, the pandemic reversed some gains.
  - Most global inequality now stems from differences within countries rather than between countries.

### Policy recommendations
- Structural reforms to restore allocative efficiency:
  - Promote market competition, trade openness, financial accessibility, and labor market flexibility to boost TFP by alleviating institutional and financial barriers to efficient allocation of capital and labor.
  - Exercise caution with industrial policy: poorly designed industrial policies may impede resource allocation to more productive firms or sectors.
- Labor supply and participation:
  - Facilitate flow and integration of migrant workers and enhance labor market integration policies.
  - Boost labor force participation among older workers in advanced economies through retirement reforms and labor market programs.
  - Encourage participation of women in emerging market economies via expanded education enrollment and childcare support; reduce social barriers and gender discrimination to improve talent allocation.
- Capital formation and investment:
  - Reform mechanisms for restructuring and insolvency and eliminate debt bias in corporate tax policies to support business investment in emerging market economies.
- Managing geoeconomic fragmentation:
  - Avoid damaging unilateral trade and industrial policies to lessen negative growth impacts.
- Harnessing AI and innovation:
  - Strengthen regulatory frameworks, including intellectual property protection, and revisit redistributive and adjustment programs to ensure AI benefits are shared fairly and widely.
  - Policies geared toward promoting innovation are crucial for long-term global growth prospects.

### Box 3.2 — Distributional Implications of Medium-Term Growth Prospects
- Overview:
  - Projection for global inequality combines within-country and between-country inequality projections derived from the WEO; results show no or only modest expected recoupment in the medium term.
  - Small within-country inequality improvements are insufficient to offset slowdown in between-country convergence.
- GDP as a proxy for welfare; complementary welfare measure:
  - GDP is used as a proxy for welfare but may omit unpaid household work and environmental costs.
  - Jones and Klenow (2016) welfare measure complements consumption with life expectancy, leisure, and (less) inequality.
  - Historically, welfare growth exceeded GDP growth, mostly due to life expectancy improvements; both GDP and welfare growth are predicted to fall postpandemic.
  - Welfare growth is expected to deteriorate more than GDP growth, driven by stalled life expectancy and within-country inequality, leading to welfare divergence.
- Inequality projections and drivers:
  - Growth slowdown has implications for income distribution between countries, global income distribution, and broader welfare measures.
  - Worsening geoeconomic fragmentation would likely worsen global inequality unless offset by large within-country improvements.
- AI: exposure, complementarity, and distributional risks:
  - IMF staff extend AI “exposure” with AI complementarity to assess job benefits or risks.
  - Share of jobs susceptible to AI:
    - Approximately 60 percent of jobs in advanced economies.
    - 40 percent in emerging market economies.
    - 26 percent in low-income countries.
  - In advanced economies, AI may enhance productivity in half of exposed jobs and automate the other half, raising risks to labor demand and wages.
  - Emerging market and developing economies are less likely to face immediate disruption but may gain less from AI due to infrastructure and skills gaps, risking increased cross-country inequality.
- Model framework and calibration:
  - Channels: labor displacement, AI complementarity with skills, and productivity gains.
  - Model calibrated to the United Kingdom; two scenarios: high complementarity, and high complementarity plus high productivity.
- Model results for the United Kingdom:
  - High complementarity scenario: output increases by almost 10 percent in the transition to a new steady state via capital deepening and a small TFP increase.
  - High complementarity and high productivity: output expands by 16 percent; TFP increases by almost 4 percent. Gains occur mainly in the first decade.
  - Income effects: incomes rise for all workers (2 percent for low-income workers to almost 14 percent for high-income workers), increasing income inequality.
- Cross-country differences in potential AI gains:
  - Productivity gains from AI in the United Kingdom estimated at 0.9 to 1.5 percent a year.
  - Many emerging market and developing economies have potential gains less than half those for the United Kingdom.
  - Share of workers in high-exposure and high-complementarity occupations:
    - 27 percent in advanced economies.
    - 16 percent in emerging markets.
    - 8 percent in low-income countries.
  - For the global economy, AI could boost productivity gains by 0.1 percent to 0.8 percent annually over a decade.
  - Uneven geographic distribution of gains underscores the need for international cooperation to improve AI readiness and integration.

*Italic: Source — ch3 - Introduction (World Economic Outlook, April 2024).*

### Introduction

### CHAPTER 3 — Introduction

### Overview and authorship
- Authors: Nan Li (co-lead), Chiara Maggi, Diaa Noureldin (co-lead), Cedric Okou, Alexandre B. Sollaci, and Robert Zymek, with support from Shrihari Ramachandra, Pablo Vega, Yarou Xu, and Dennis Zhao.
- External consultant: Peter Klenow.
- Support: Macroeconomic Policy in Low-Income Countries program of the UK’s Foreign, Commonwealth and Development Office (FCDO) and Macroeconomic Research on Climate Change and Emerging Risks in Asia program of the Ministry of Economy and Finance of the Government of Korea.
- Note: The views expressed do not necessarily represent the views of the supporting partners.

### Key questions addressed
- What are the insights from forecasts? How did forecasters’ views on medium-term growth evolve, and what do they imply about income inequality and convergence?
- How did we get here? What factors account for the decline in actual growth over the past two decades? What role did demographics and private investment play? To what extent have changes in allocative efficiency affected productivity growth?
- Where is growth heading? What are potential trajectories for medium-term growth given demographic trends and prevailing economic forces such as higher debt burdens, geoeconomic fragmentation, and the emergence of artificial intelligence (AI)? What policies could enable a return to higher growth rates seen in the two decades preceding the pandemic?

### Main findings
- The decline in medium-term growth projections is widespread, reflecting secular forces rather than forecaster pessimism.
  - Expectations for medium-term growth have been revised downward across all income groups and regions, most significantly in emerging market economies.
- Actual growth has similarly declined, largely because of TFP growth dynamics.
  - In advanced economies, productivity growth started to decrease before the global financial crisis.
  - In emerging market and developing economies, TFP growth rose before the crisis and then fell, mirroring the globalization cycle.
  - Changes in TFP growth have accounted for more than half of the decline in advanced and emerging market economies and nearly all of the decline in low-income countries.
- Increased misallocation of capital and labor among firms has exerted a drag on TFP of 0.6 percentage point a year in the economies considered in the analysis.
  - This suggests TFP growth could have been 50 percent higher if misallocation had not increased.
  - Most of this misallocation increase stems from uneven firm productivity growth within sectors, requiring reallocation of capital and labor that was impeded by economic frictions.
  - Two-thirds of misallocation at any time can be attributed to persistent structural frictions, which policy measures can address.
- Reduced private capital formation since the global financial crisis in many advanced and emerging market economies has also contributed to the growth decline.
  - Deterioration in firms’ valuations relative to the cost of capital and rising corporate leverage are the two most important firm-specific factors contributing to the decline in business investment.
  - At the macroeconomic level, lackluster growth performance and uncertainty have inhibited investment in advanced economies.
- Demographic pressures weighing on labor supply are expected to intensify in the medium term in most advanced economies and major emerging markets.
  - By 2030, global labor supply growth is projected to be 0.3 percent, less than a third of its average in the decade before the pandemic.
- Policy conclusion: Returning global growth to the historical (2000–19) annual growth average of 3.8 percent requires growth-enhancing policies and reforms to improve allocative efficiency and labor participation, facilitate cross-border trade and knowledge exchange, enhance innovation capabilities, and maximize the capacity to benefit from technological advances such as AI.
  - Based on projected demographic trends and conservative assumptions about technological progress, global growth in the medium term could fall below 3 percent without such policies.

### Insights from medium-term forecasts
- Five-year-ahead WEO growth projections show a broad-based downturn in growth prospects since 2008 affecting nearly 82 percent of economies, including the world’s largest.
- The five largest emerging market economies—Brazil, China, India, Indonesia, and Russia—contributed approximately 0.8 percentage point of the 1.8 percentage point drop in projected global growth.
- The downshift is evident across regions and most pronounced for East Asia and the Pacific.
- Examination of forecast errors shows no evidence of a pessimism bias in forecasters’ five-year-ahead forecasts (Online Annex Figure 3.1.1).
- WEO medium-term growth forecasts are generally well aligned with projections of potential output growth (Online Annex Figure 3.1.2); deviations occur mainly after crises when forecasters expect faster growth to close large output gaps.
- Catch-up (income convergence) explains only about a quarter of the projected global growth decline since 2008 (see Box 1.1 of the October 2023 WEO).
- Measures in Box 3.2 suggest the pace of convergence in income and social welfare is slowing or potentially reversing over the medium term.

### How did we get here? — Growth decomposition and TFP
- Global growth accelerated in the early 2000s until the 2008 global financial crisis and has declined since then; the pattern aligns with medium-term projection dynamics.
- In per capita terms, GDP growth followed a similar trend across country groups, with a modestly smaller postcrisis decline as population growth slowed.
- For all country groups, shifts in growth have been primarily the result of changes in TFP growth.
  - Advanced economies: annual TFP growth fell from 1.3 percent during 1995–2000 to 0.2 percent after the pandemic, accounting for half of the GDP growth reduction.
  - Emerging market economies: TFP growth dropped from 2.5 percent during 2001–07 to 0.7 percent after the pandemic.
  - Low-income countries: TFP growth fell from 2 percent during 2001–07 to nearly zero after the pandemic.
- Slower capital formation after 2008 for advanced economies and since 2013 for emerging market economies has also contributed to the global growth slowdown.
- A consistent decline in the labor contribution—driven by aging populations and retreating labor force participation in major economies—has further suppressed growth.

### A demographic drag on labor supply
- The working-age population (ages 15–64) growth has slowed in about 92 percent of the global economy since 2008 and has been negative in about 44 percent.
- Several large economies (Canada, China, United Kingdom, United States) experienced the demographic turning point around the time of the global financial crisis.
- Nearly two in every three new entrants to the global workforce over the medium term will come from India and sub-Saharan Africa.
- Shift-share analysis of labor force participation (2008–21):
  - Aggregate participation rates declined in most world regions except Advanced Asia and the Pacific, the Middle East and North Africa, Europe, and Canada.
  - The drag from aging is visible in all advanced economies and China, and to a lesser extent in Latin America.
  - Advanced economies—except the United States—increased within-group labor force participation, largely via gains in female participation and higher participation of older workers.
  - Decline in male participation was a drag in emerging market economies and the United States.
- The pandemic exacerbated drops in participation between 2019 and 2020, with partial recovery in 2021; participation remained broadly lower than in 2019 in Latin America (about 1.9 percentage points) and the United States (about 1.4 percentage points).
- Policy associations with participation (OECD sample, associational results):
  - Reduced unemployment benefits and lower labor taxes are associated with higher participation for men aged 25 to 54.
  - Expansion in secondary education enrollment is associated with higher future participation for women aged 25 to 54.
  - Labor market programs and childcare programs are supportive for female participation.
  - Retirement-age reforms and spending on labor market programs are associated with higher participation for older workers (ages 55 to 64).

### Anemic private capital formation
- Business investment—the bulk of total investment—in OECD economies tumbled after 2008 and in 2021 fell by about 40 percent of its pre-global-financial-crisis trend.
- The analysis examines whether the slowdown in economic activity since the 2008 global financial crisis impeded economy-wide business investment using “narrative fiscal shocks” and other approaches (see figures and Online Annex).
- Predicted values for investment growth are obtained by multiplying the estimated investment-output elasticity reported in Online Annex Table 3.2.3 by output growth; weaker economic activity is defined as a deceleration in output growth.
- The pre-GFC trend is shown against actual and predicted real business investment growth for 21 OECD economies (Figure 3.8); the confidence band denotes a 90 percent confidence interval.

_Italic: Source — ch3 - Introduction (World Economic Outlook, April 2024)._

### CHAPTER 3 SLOWDOWN IN gLObaL MEDIUM-TERM gROWTH: WHaT WILL IT TaKE TO TURN THE TIDE?

### CHAPTER 3 SLOWDOWN IN gLObaL MEDIUM-TERM gROWTH: WHaT WILL IT TaKE TO TURN THE TIDE?

### Investment shortfall and firm-level determinants
- Instrumental-variable estimate: for every 1 percentage point decline in output growth that is not triggered by a contraction in business investment, there is a corresponding 2 percentage point decrease in investment growth.
- As of 2021, about half of the shortfall in business investment since 2008 can be linked to weaker economic activity (comparison with precrisis trend).
- Firm-level sample and measurement:
  - Analysis uses publicly listed firms in 32 advanced economies and 13 emerging markets.
  - Net investment rate defined as investment divided by lagged capital stock net of depreciation; investment and capital stock figures account for intangibles.
- Aggregate investment-rate changes since 2008:
  - Overall investment rate declined, on average, by about 2.3 percentage points in advanced economies.
  - Overall investment rate declined by about 2 percentage points in emerging markets.
  - Regression analysis explains more than half of the decline in advanced economies and virtually all of the decline in emerging markets using included determinants.
- Key firm-level determinants and their changes since 2008:
  - Tobin’s q (market value relative to cost of capital) decreased by 10 to 30 percent on average, contributing the bulk of the explained decline in investment in both AEs and emerging markets.
  - Emerging markets experienced a 20 percent average increase in leverage after 2008, materially contributing to the investment fall.
  - Investment rates increase with Tobin’s q, profits, and cash stock; decrease with higher corporate leverage and the cost of debt.
- Other macro factors:
  - The decline in GDP growth since 2008 helps explain the investment decline even after controlling for firm-level determinants.
  - Rising uncertainty after 2008 makes a smaller but still significant contribution to the investment decline in advanced economies.
  - Increased capital inflows since 2008 have been positive for investment in emerging markets.

### Productivity trends and the role of resource misallocation
- TFP growth has slowed over the past two to three decades; contributors include waning ICT gains, declining business dynamism, tighter credit conditions, and slower cross-border capital and trade expansion.
- Allocative efficiency and implications:
  - Allocative efficiency measures the extent to which capital and labor are allocated to the most productive firms; a decline reduces TFP growth.
  - Using methods pioneered by Hsieh and Klenow (2009) and refined by Bils, Klenow, and Ruane (2021), allocative efficiency declined during 2000–19 in most countries in a sample of 15 advanced and 5 emerging market economies.
  - The median country experienced an average annual drag on TFP growth of about 0.9 percentage point from declining allocative efficiency.
  - For the median advanced economy, the drag was 0.5 percentage point; given that the median advanced economy saw TFP growth of only 0.5 percent during 2000–19, increased misallocation may have halved its TFP growth.
  - United States was a notable exception: improvements in allocative efficiency helped boost annual TFP growth by 0.8 percentage point over the period.
- Decomposition of allocative-efficiency decline:
  - Changing sector shares in GDP contributed only about 30 percent of the annual drag on TFP; the remainder is attributable to within-sector developments.
  - Structural transformation toward services (which display more inefficiency than goods) can reduce overall allocative efficiency.
- Firm-level dispersion and dynamics:
  - The dispersion of firms’ real productivity rose significantly leading up to the global financial crisis and remains elevated.
  - Wider dispersion implies faster-growing firms should attract capital and labor, but frictions slow adjustment, causing an initial decline in allocative efficiency.
  - Recovery is slow: it takes 9–11 years for allocative efficiency to return halfway to its long-term fundamental level after shocks.
  - For the economies analyzed, about one-third of measured misallocation is attributable to transitory factors; two-thirds has structural roots.
- Cross-country variation and policy links:
  - A country’s structural allocative efficiency rises with market entry and competition, trade openness, financial access, and labor market flexibility.
  - No systematic evidence that changes in structural policies during 2000–19 explain the observed decline in allocative efficiency for the sample as a whole.
  - Policy scenario: if countries with allocative efficiency below the United States reduced their gaps in structural policies by 15 percent over 10 years, medium-term TFP growth could be boosted by 0.7 percentage point.

### Where is growth heading? Baseline medium-term projections (to 2030)
- Projection approach:
  - Labor force participation forecasts use a cohort-based approach with United Nations demographic projections to estimate potential employment growth, assuming stable employment rates.
  - Capital growth merges WEO public investment forecasts with the chapter’s estimates of the medium-term private investment rate.
  - TFP growth projects sectoral allocative efficiency moving gradually toward its estimated long-term level and reaching its half-life in the medium term; efficient TFP growth (net of misallocation) follows historical trend.
- Labor supply and contribution to global GDP growth by 2030:
  - By 2030, the annual contribution of labor supply to global GDP growth is expected to decrease to 0.2 percentage point, only a quarter of its 2000–19 average contribution.
  - This reflects a projected 0.3 percent growth of potential labor supply in 2030.
  - Regional variation in projected potential labor-supply growth for 2030:
    - Low-income countries: 2.1 percent growth in labor supply.
    - Emerging market economies, excluding China: (regional variation noted; sample details included in Online Annex 3.3).
  - The slowdown in labor’s contribution reflects falling participation rates that dampen the effect of population growth on labor supply, implying a need for job creation especially in countries with robust labor-supply growth.

*Source: CHAPTER 3 SLOWDOWN IN gLObaL MEDIUM-TERM gROWTH: WHaT WILL IT TaKE TO TURN THE TIDE? (IMF, April 2024).*

### 0.9 percent, and in the US by 0.5 percent, whereas

### ch3 - 0.9 percent, and in the US by 0.5 percent, whereas

### Contributions to medium-term global growth (baseline)
- Labor supply:
  - A sharp reduction in participation will cause labor supply to contract by 0.6 percent in China and by 0.5 percent in the EU.
- Capital:
  - Capital’s contribution to growth is expected to be 1.7 percentage points, compared with the 2000–19 average contribution of 2.1 percentage points.
  - Public investment accounts for 30 percent of emerging market and developing economies’ overall capital.
  - Advanced economies are expected to see a modest increase in public investment, but its growth impact will be minimal given its small share in overall investment.
- Total Factor Productivity (TFP):
  - The TFP growth contribution is expected to decline to 0.9 percentage point by 2030, down from the 2000–19 average of 1.0 percentage point.
  - The net effect is a decline in the TFP growth rate by 0.1 percentage point from its two-decade average prior to the pandemic.
  - Factors cited: increasing difficulty of generating new ideas, slower growth of research employment, a plateau in educational attainment, and slower catch-up.
  - Major technological advances, particularly in AI, could increase TFP growth substantially.
- Aggregate baseline projection:
  - When the contributions of the three factors are summed, the world’s growth rate is projected at 2.8 percent in 2030 under the baseline scenario.
  - Historical (2000–19) annual average growth was 3.8 percent.

### Alternative scenarios (impacts relative to baseline)
- Overall range:
  - Medium-term growth effects range from 1.2 percentage points above to 0.8 percentage point below the baseline.
  - Larger effects are possible if scenarios occur simultaneously; figures are indicative given high uncertainty.
- Policies to increase labor force participation:
  - Assumes countries increase labor force participation rates by 3.2 percentage points (the median increment if all countries converged to the best policies).
  - Could increase labor supply growth by about 0.3 percentage point, contributing 16 basis points to global growth.
- A migration boost to advanced economies’ labor supply:
  - Assumes higher flows and enhanced labor market integration translating into an increase in labor supply equivalent to 1 percent of advanced economies’ projected labor force in 2030.
  - Could add 20 basis points to global growth.
- Structural reforms reducing misallocation:
  - Assumes countries close 15 percent of their policy gap with the United States in areas such as product and labor market policies, trade openness, and financial deepening over the medium term.
  - Expected to enhance TFP growth by 0.7 percentage point and add 1.2 percentage points to global growth.
- Improved talent allocation in emerging market and developing economies:
  - If talent allocations follow the trend in the United States over past decades, global growth could be boosted by 0.25 percentage point (a quarter of a percentage point).
- AI adoption:
  - Estimated global growth impact varies from 10 to 80 basis points in the medium term, depending on adoption and whether AI replaces or augments workers.
- Legacy of high public debt:
  - Persistent elevated public debt could reduce medium-term growth by an estimated 5 to 15 basis points.
  - Scenarios simulated: continued debt increase with stable public deficits; two debt-stabilization scenarios where increased interest payments are offset by reducing transfers or public investment.
- Geoeconomic fragmentation:
  - Limited “friend-shoring” scenarios could reduce growth by 10 basis points.
  - A more extensive reshoring scenario could lower medium-term growth by 80 basis points.
  - A greater loss could result from reduced trade-associated knowledge spillovers and productivity loss, not accounted for in the simulation.

### Key findings and risks
- Declining TFP, driven by increased resource misallocation and slower efficient TFP growth, is a central driver of the slowdown.
- Shrinking working-age populations in major economies and lackluster business investment also contribute to weaker medium-term growth.
- Without timely policy interventions and technological gains (notably from AI), global growth is likely to remain well below its prepandemic historical average in the medium term.
- Between-country convergence:
  - Cross-country convergence took place during 2008–19 and was fastest during 2008–12; the rate turned positive after the pandemic.
  - Current projections point to no convergence over the medium term.
- Global inequality:
  - Although inequality decreased since the mid-2000s, the pandemic reversed some gains.
  - Most global inequality now stems from differences within countries rather than between countries.

### Policy recommendations
- Structural reforms to restore allocative efficiency:
  - Promote market competition, trade openness, financial accessibility, and labor market flexibility to boost TFP by alleviating institutional and financial barriers to efficient allocation of capital and labor.
  - Caution on industrial policy: poorly designed industrial policies may impede resource allocation to more productive firms or sectors.
- Labor supply and participation:
  - Facilitate flow and integration of migrant workers and enhance labor market integration policies.
  - Boost labor force participation among older workers in advanced economies through retirement reforms and labor market programs.
  - Encourage participation of women in emerging market economies via expanded education enrollment and childcare support; reduce social barriers and gender discrimination to improve talent allocation.
- Capital formation and investment:
  - Reform mechanisms for restructuring and insolvency and eliminate debt bias in corporate tax policies to support business investment in emerging market economies.
- Managing geoeconomic fragmentation:
  - Avoid damaging unilateral trade and industrial policies to lessen negative growth impacts.
- Harnessing AI and innovation:
  - Strengthen regulatory frameworks, including intellectual property protection, and revisit redistributive and adjustment programs to ensure AI benefits are shared fairly and widely.
  - Policies geared toward promoting innovation are crucial for long-term global growth prospects.

*Source: IMF staff calculations.*

### Box 3.2. Distributional Implications of Medium-Term Growth Prospects

### Box 3.2. Distributional Implications of Medium-Term Growth Prospects

### Overview
- A projection for global inequality is created by combining within-country and between-country inequality projections derived from the World Economic Outlook (WEO).
- Depending on the measure analyzed, there is either no or only a modest expected recoupment in the medium term.
- Small within-country inequality improvements are not sufficient to offset the expected slowdown in between-country inequality convergence.

### GDP as a proxy for welfare; complementary welfare measure
- The analysis uses GDP as a proxy for welfare, while noting this association could be flawed because it does not include unpaid household work or the environmental cost of economic growth.
- Jones and Klenow (2016) propose a welfare measure based on lifetime expected utility that complements consumption with life expectancy, leisure, and (less) inequality.
- Historically, welfare growth has exceeded GDP growth, driven mostly by life expectancy improvements.
- Across regions, both GDP and welfare growth are predicted to fall in the postpandemic period.
- Welfare growth is expected to deteriorate more than GDP growth, driven by stalled dimensions such as life expectancy and within-country inequality, leading to welfare divergence between countries.

### Inequality projections and drivers
- The growth slowdown has significant implications for:
  - The distribution of income between countries.
  - Global income distribution.
  - A broader welfare measure that incorporates life expectancy, leisure, and inequality.
- If factors such as geoeconomic fragmentation worsen the distribution of income between countries, global inequality and the distribution of welfare will likely worsen unless those factors significantly improve income distribution within countries and other welfare dimensions (such as life expectancy).

### Artificial intelligence (AI): exposure, complementarity, and distributional risks
- IMF staff extend the AI “exposure” concept with AI complementarity to assess the likelihood that jobs will either benefit from AI or be at risk.
- There is significant disparity in AI exposure between country groups:
  - Approximately 60 percent of jobs in advanced economies are susceptible to changes as a result of AI.
  - 40 percent in emerging market economies.
  - 26 percent in low-income countries.
- In advanced economies, AI is expected to enhance productivity in half of these exposed jobs; the other half may face automation risks, reducing labor demand and wages and potentially leading to job obsolescence.
- Emerging market and developing economies are less likely to experience immediate disruption but also may gain less from AI due to gaps in infrastructure and skills, raising concerns that AI could exacerbate inequality across countries over time.

### Model framework and calibration
- The model captures AI effects through three channels: labor displacement, AI complementarity with skills, and productivity gains.
  - Labor displacement: tasks shift from humans to AI-driven systems, improving task completion efficiency.
  - AI complementarity: tasks highly complementary with AI may benefit from integration.
  - Productivity gains: AI adoption may lead to broad-based productivity gains, boosting investment and overall labor demand.
- The model is calibrated to the United Kingdom, a country highly exposed to AI adoption with available household asset-holding data.
- Two scenarios are considered:
  - High complementarity.
  - High complementarity and high productivity (which adds an overall productivity boost).

### Model results for the United Kingdom
- Scenario outcomes (change between initial and final steady state):
  - In the first scenario (high complementarity):
    - Output increases by almost 10 percent as the UK adjusts to the new steady state through capital deepening and a small increase in total factor productivity (TFP).
  - In the second scenario (high complementarity and high productivity):
    - Output expands by 16 percent.
    - Total factor productivity increases by almost 4 percent.
  - These gains occur primarily in the first decade of transition.
- Income distribution effects:
  - Incomes for all workers increase, ranging from 2 percent for low-income workers to almost 14 percent for high-income workers, leading to higher income inequality.

### Cross-country differences in potential AI gains
- Productivity gains from AI are expected to range from 0.9 to 1.5 percent a year in the United Kingdom, reflecting its digital infrastructure, skilled labor force, innovation ecosystem, and regulatory framework.
- Many emerging market and developing economies are estimated to have potential gains less than half those for the United Kingdom, owing largely to a smaller share of workers in high-exposure and high-complementarity occupations.
  - Share of workers in high-exposure and high-complementarity occupations:
    - 27 percent in advanced economies.
    - 16 percent in emerging markets.
    - 8 percent in low-income countries.
- For the global economy, estimates suggest AI could boost productivity gains by 0.1 percent to 0.8 percent annually over a decade.
- The uneven geographic distribution of these gains underscores the need for international cooperation to improve AI readiness and integration in less-prepared nations to help reduce global inequalities.

*Source: Box 3.2. Distributional Implications of Medium-Term Growth Prospects, World Economic Outlook chapter content.*

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_Source: https://www.imf.org/-/media/files/publications/weo/2024/april/english/ch3.pdf_