## World Economic Outlook — April 2024 (selected chapters and appendices) ## Source details **Canonical URL:** [World Economic Outlook — April 2024 (selected chapters and appendices)](https://www.imf.org/-/media/files/publications/weo/2024/april/english/text.pdf) ## Other formats - [Markdown version](/-/media/files/publications/weo/2024/april/english/text.pdf.md) - [Structured JSON version](/-/media/files/publications/weo/2024/april/english/text.pdf.json) --- ### Global outlook and headline projections - Global growth: 2023 = 3.2 percent; 2024 = 3.2 percent; 2025 = 3.2 percent. - Global headline inflation (World consumer prices): 2023 = 6.8 percent; 2024 = 5.9 percent; 2025 = 4.5 percent. - Median headline inflation decline: from 2.8 percent at end-2024 to 2.4 percent at end-2025. - Latest five-year forecast for global growth: 3.1 percent. - World trade volume (goods and services): 2023 = 0.3 percent; 2024 = 3.0 percent; 2025 = 3.3 percent. - Oil price assumptions: $78.61 a barrel in 2024; $73.68 a barrel in 2025. - Real effective exchange rates assumed constant at January 30, 2024–February 27, 2024 average levels (exceptions for ERM II participants relative to the euro). ### Key numerical assumptions and financial market baselines - Growth working hypotheses in Preface: 1.0 percent in 2024 and 1.1 percent in 2025 (working hypotheses rather than forecasts). - Three-month government bond yields (assumptions): - United States: 5.2 percent (2024) and 4.1 percent (2025). - Euro area: 3.5 percent (2024) and 2.6 percent (2025). - Japan: 0.0 percent (2024) and 0.1 percent (2025). - Ten-year government bond yields (assumptions): - United States: 4.1 percent (2024) and 3.7 percent (2025). - Euro area: 2.5 percent (2024) and 2.6 percent (2025). - Japan: 1.0 percent (2024) and 1.1 percent (2025). - Assumed US dollar–SDR conversion rates: 1.329 (2024) and 1.331 (2025). - Assumed US dollar–euro conversion rates: 1.078 (2024) and 1.073 (2025). - Assumed yen–US dollar conversion rates: 148.5 (2024) and 146.4 (2025). ### Risks, uncertainty, and probabilistic outlook - Risk distribution for global growth: broadly balanced; probability global growth falls below 2.0 percent in 2024 ≈ 10 percent (down from 15 percent in October 2023); same ≈ 10 percent for 2025. - Probability global per capita real GDP contracts in 2024: below 5 percent. - Fan-chart 70 percent ranges: - 2024 global growth between 2.4 percent and 4.1 percent (70 percent probability). - 2025 global growth between 2.2 percent and 4.3 percent (70 percent probability). - Box 1.2 global inflation uncertainty: - 70 percent probability that 2024 headline inflation will be about 1.3 percentage points higher or lower than projected. - Probability headline inflation higher in 2024 than in 2023: about 20 percent. - Probability core inflation higher in 2024 than in 2023: less than 10 percent. ### Major downside risks highlighted - New commodity price spikes from geopolitical tensions (including the war in Ukraine and the conflict in Gaza and Israel) that could raise interest rate expectations and reduce asset prices. - Persistent core inflation where labor markets remain tight, sustaining elevated policy rates and financial stress. - A larger downturn in China without a comprehensive property-sector response, with negative spillovers. - Excessively sharp fiscal consolidation that weakens activity and reform momentum. - Geoeconomic fragmentation intensifying, raising barriers and slowing the supply side. ### Major upside scenarios highlighted - Looser fiscal policy than assumed could raise activity short term but increase borrowing costs later. - Faster-than-expected disinflation or labor force participation gains allowing earlier central bank easing. - Artificial intelligence (AI) and stronger structural reforms could spur productivity and growth. --- ### Policy guidance and multilateral priorities - Monetary policy: - Near-term priority: ensure inflation “touches down smoothly, by neither easing policies prematurely nor delaying too long and causing target undershoots.” - Where core inflation persists above target-consistent levels, higher real interest rates may be necessary. - Where inflation expectations and underlying gauges clearly decline toward target, avoid delaying nominal policy rate cuts excessively to prevent unintended real-rate tightening. - Fiscal policy: - Renewed focus on medium-term fiscal consolidation to rebuild buffers, enable priority investments, and ensure debt sustainability. - Calibration: gradual and sustained adjustment preferred where possible; front-loaded adjustment when market access is lost. - Protect targeted support for the most vulnerable and preserve priority investments during consolidation. - Macrofinancial policy: - Strengthen supervision (including implementation of Basel III), recalibrate macroprudential policies where needed, and deploy liquidity support promptly while mitigating moral hazard. - In shallow FX markets with large foreign-currency debts, consider FX intervention or capital flow management measures combined with macroprudential policies. - Multilateral cooperation: - Coordinate to limit geoeconomic fragmentation and climate-change costs, accelerate green transition, facilitate debt restructuring, and support technology transfer for green investments. - Specific guidance on fossil-fuel subsidies: “Cutting harmful fossil fuel subsidies can help create the necessary fiscal room for further green investments.” --- ### Chapter 1 — Global Prospects and Policies: selected findings ### Growth and inflation by country groups and major economies - World output (Q4 over Q4): 2023 = 3.2; 2024 = 3.2; 2025 = 3.1. - Advanced economies growth: 2023 = 1.6 percent; 2024 = 1.7 percent; 2025 = 1.8 percent. - Emerging Market and Developing Economies aggregate: 2023 = 4.5 percent; 2024 = 4.3 percent; 2025 = 4.1 percent. - Selected country projections (annual): - United States: 2023 = 2.5 percent; 2024 = 2.7 percent; 2025 = 1.9 percent. - Euro area: 2023 = 0.4 percent; 2024 = 0.8 percent; 2025 = 1.5 percent. - China: 2023 = 5.2 percent; 2024 = 4.6 percent; 2025 = 4.1 percent. - India (fiscal year): 2023 = 7.8 percent; 2024 = 6.8 percent; 2025 = 6.5 percent. ### Financial conditions, debt burdens, and fiscal projections - Low-income countries: interest payments on debt estimated to average 14.3 percent of general government revenues in 2024, about double the level 15 years ago. - Structural fiscal-balance-to-GDP ratio projected to rise by 1.9 percentage points in the United States in 2024 and by 0.8 percentage point in the euro area in 2024. - Advanced-economy fiscal stance expected to tighten in 2024 and to a lesser extent in 2025–26; EMDEs projected to be broadly neutral on average in 2024 with tightening about 0.2 percentage point in 2025. ### Commodity price baselines and movements - Commodity price projections (averages/changes for 2024): - Fuel commodities projected to fall in 2024 by, on average, 9.7 percent. - Oil prices projected to fall by about 2.5 percent in 2024. - Coal projected to decline by 25.1 percent in 2024. - Natural gas projected to decline by 32.6 percent in 2024. - Base metals expected to fall by 1.8 percent in 2024. - Food commodity prices predicted to decline by 2.2 percent in 2024. --- ### Chapter 2 — Feeling the Pinch? Monetary policy transmission through housing markets ### Research focus and empirical approach - Questions: where are real estate and mortgage markets now; conceptual housing channels of monetary transmission; cross-country variation; have housing channels weakened? - Data and methods: monetary policy surprises versus analyst predictions; prevalence of fixed-rate mortgages (FRMs); regulatory loan-to-value (LTV) limits; household debt; local house-price and supply indicators; local-projection IV framework for panel of 33 economies covering 1998:Q4–2023:Q1. ### Seven housing-related transmission channels (conceptual) - Channel 1 — Cash flow channel (adjustable-rate borrower cash-flow effects). - Channel 2 — Expectations/risk premium channel. - Channel 3 — Wealth channel. - Channel 4 — Collateral channel. - Channel 5 — Interest rate channel (mortgage-rate pass-through). - Channel 6 — Bank lending channel. - Channel 7 — Balance sheet channel. ### Key empirical findings (heterogeneity and magnitude) - Fixed-rate mortgages (FRMs): - High share of FRMs significantly dampens transmission of monetary policy to consumption relative to low-FRM countries; differences become significant after five quarters. - No significant differences in transmission to house prices between high-FRM and low-FRM countries. - Regulatory LTV limits: - LTV restricted (below 100 percent) vs LTV not restricted: eight quarters after a 100 basis point increase in policy rates, house prices drop by 1 percentage point when LTV restricted and by 4 percentage points when LTV not restricted. - Consumption effect materializes faster when LTV limits are not restricted; by four quarters the effect when LTV restricted is about half that when LTV not restricted. - Household debt: - Eight quarters after a policy change, nominal house prices respond about 3 percentage points more when household debt ratios are above the sample median. - Consumption responses are faster if household debt is higher (differences diminish after three quarters). - Local housing supply and overvaluation: - Supply-restricted areas (proxied by population density): additional nominal house-price response of about 3 percentage points after eight quarters to a 100 basis point tightening/loosening relative to less restricted areas; real GDP per capita undergoes an additional 2 percentage point peak change. - Overvalued areas: peak fall (rise) in nominal house prices about 1.5 percentage points greater; real GDP per capita declines (rises) an extra 1 percentage point in overvalued regions. - Asymmetry: - Supply constraints and overvaluation matter more when policy tightens than when it eases; statistical rejection of symmetry for house prices in first two quarters. ### Model simulations and interactions - Two-agent New Keynesian model simulations quantify complementarities: - Moving from high to low FRMs given loose LTV limits: transmission rises by 17 percent. - Moving from high to low FRMs given tight LTV limits: transmission rises by 13 percent. - Moving from loose to tight LTV limits given low FRMs: transmission rises by 23 percent. - Moving from loose to tight LTV limits given high FRMs: transmission rises by 19 percent. - Weakest transmission occurs with restrictive LTV limits and highly prevalent FRMs. ### Recent evolution and policy implications - Trends since global financial crisis and pandemic: increased prevalence of FRMs in many countries, tighter or stable LTV limits, migration to less-supply-constrained areas—factors that weaken housing-channel transmission in many countries. - Policy recommendations: - Macroprudential authorities: borrower-based macroprudential measures (including debt-service-to-income caps) to preserve financial stability and allow monetary policy to focus on demand and price pressures. - Monetary authorities: deep, country-specific understanding of housing channels to calibrate policy; monitor household debt service and housing developments to detect overtightening risks. - Caution: fixation periods on FRMs may be short; as FRMs reset, transmission could intensify and depress consumption, risking financial instability if defaults rise. --- ### Chapter 3 — Slowdown in global medium-term growth: drivers and policy levers ### Headline medium-term outlook and projections - Global growth baseline for 2029: 3.1 percent (unchanged since October 2023 WEO). - Without timely policy interventions or technology boosts, world growth could be only 2.8 percent by 2030. - Global labor supply growth projected to be 0.3 percent by 2030 (less than a third of its pre-pandemic decade average). - World growth rate projected at 2.8 percent in 2030 under baseline; historical (2000–19) annual average = 3.8 percent. ### Main drivers of the slowdown - Total factor productivity (TFP) declines: - Advanced economies: annual TFP growth fell from 1.3 percent during 1995–2000 to 0.2 percent after the pandemic. - Emerging markets: 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. - Increased misallocation of capital and labor: - Misallocation drag on TFP: median country ≈ 0.9 percentage point annual drag during 2000–19; median advanced economy drag ≈ 0.5 percentage point. - Increased misallocation accounts for part of the TFP slowdown; two-thirds of misallocation is structural. - Investment shortfalls: - About 2.3 percentage point decline in overall investment rate in advanced economies since 2008; about 2 percentage points in emerging markets. - Lower Tobin’s q and rising corporate leverage contributed to reduced investment. ### Demographics and labor participation - Since 2008, working-age population growth slowed in about 92 percent of the global economy and was negative in about 44 percent. - By 2030, labor’s contribution to global GDP growth expected to decline to 0.2 percentage point (reflecting 0.3 percent growth of potential labor supply in 2030). - Two-thirds of new entrants over the medium term to global workforce come from India and sub-Saharan Africa. ### Policy levers and scenario outcomes - Policies to raise medium-term growth: - Improve allocative efficiency (reduce misallocation), increase labor force participation, boost innovation and technology diffusion, and facilitate trade and knowledge flows. - Scenario impacts (examples): - Structural reforms closing 15 percent of the policy gap with the United States could enhance TFP growth by 0.7 percentage point and add 1.2 percentage points to global growth. - Migration boost in advanced economies (1 percent of projected labor force in 2030) could add 20 basis points to global growth. - AI adoption scenarios: global growth impact ranges from 10 to 80 basis points depending on adoption and complementarity effects. - Distributional notes: - AI could raise wages unevenly (example box: wages increase 2 percent for low-income workers and almost 14 percent for high-income workers in modeled scenarios), increasing income inequality without complementary policies. --- ### Chapter 4 — Trading Places: real spillovers from G20 Emerging Markets ### Rising footprint and spillover magnitudes - G20 EMs’ global trade and investment footprint has almost doubled since early 2000s. - China remains the largest source of spillovers: a 1 percentage point demand shock in China leads to ≈ 0.3 percentage point higher growth in other emerging markets after three years. - Domestic growth shocks in China explain just under 5 percent of output variation in advanced economies after three years and just over 10 percent in other emerging markets. - Growth spillovers from some G20 EMs can explain almost 5 percent of GDP variation in advanced economies in some cases. ### Firm-level and GVC transmission patterns - Firm-level evidence: - A 1 percentage point unexpected increase in GDP growth in G20 EMs → almost 0.5 percentage point higher revenue growth after one year for firms more exposed to G20 EM demand; effect fades but remains ~0.25 percentage point after five years. - Firms depending on inputs from G20 EMs can experience negative spillovers from positive demand shocks in G20 EMs due to competition effects. - Trade-model (steady-state) findings: - Baseline 2.5 percent TFP shock across G20 EMs (≈ 10 percent domestic output decline): global GDP excluding G20 EMs declines ≈ 0.15 percent; about one-half attributable to China. - Spillovers from G20 EM productivity shocks have increased almost threefold since early 2000s due to deeper GVC integration. - Scenario with shocks concentrated in GVC-intensive sectors: external impacts on global GDP outside G20 EMs are about two-thirds of baseline despite smaller domestic impact. ### Sectoral employment and reallocation - Productivity shocks generate both complementarities (job gains) and competition (job losses) across sectors and countries. - Positive shocks in G20 EM manufacturing (notably China) produce both positive spillovers for some foreign sectors (computer, electronic, optical equipment; textiles) and negative spillovers for others. - Sectoral reallocation: many sectors contract (agriculture, mining, utilities, trade and services in Asia) while some manufacturing sectors (textiles, basic metals, electrical equipment) can expand. ### Can other G20 EMs support global growth if China weakens? - GIMF upside scenario (positive 5-year demand and supply shocks for G20 EMs excluding China): - Other G20 EMs’ aggregate GDP growth rises by 0.7 percentage point over WEO horizon. - Global growth accelerates by 0.5 percentage point; about 85 percent of impact driven by shock sizes, 15 percent from spillovers across EMs and to China and advanced economies. - India plays a prominent role through GVCs and demand. ### Policy implications - Countries with strong linkages to G20 EMs should build buffers, diversify output and input linkages, and pursue domestic structural policies to manage reallocation. - Avoid protectionist responses; targeted structural reforms and policies to support reallocation and workers (skills, social safety nets) recommended. - Multilateral cooperation and strengthening global financial safety nets urged to manage negative spillovers and fragmentation risks. - Domestic subsidies in G20 EMs: - Number of subsidies tripled in past decade; by 2022 about 6,000 distortive domestic subsidies in G20 EMs (Global Trade Alert). - Subsidies raise exports on the intensive margin (~10 percent higher after eight years) and increase probability of exporting by 3 percentage points. --- ### Special Feature — The Power of Prices: commodity market adjustment to shocks ### Main empirical conclusions on elasticities and dynamics - Overall: commodity demand and supply are generally price inelastic with notable differences across commodity types. - Supply elasticities: - Metals (copper, zinc) have very low supply elasticities (copper and zinc close to zero). - Cereals supply elasticity ≈ 0.6 (a 10 percent price increase raises output by 6 percent within a year). - Perennial crops (coffee, palm oil, cocoa) have smaller short-term supply elasticities; typical time to fruit: palm oil ≈ two years; cocoa ≈ five years. - Energy commodity supply elasticities intermediate between mineral and agricultural elasticities. - Demand elasticities: - Rice demand elasticity close to zero. - Crude oil and coal demand elasticities below 0.2. - Copper and zinc demand elasticities close to zero. - Lead and tin demand elasticities between 0.2 and 0.3. - Time dynamics: - Responsiveness increases over time for many commodities; metals and energy show upward-sloping supply elasticities over time; agricultural supply responses often peak within two to three years for perennials and are flatter for annuals. ### Policy implications - Countries exposed to commodities with low elasticities (especially metals) should build fiscal buffers and monetary policy space to prepare for larger shock impacts. - Replacing broad energy and agricultural subsidies with targeted transfers could increase demand and supply elasticities and reduce price volatility. - International trade plays a prominent role in smoothing shocks and buffering economic impact; trade openness is particularly important amid rising geopolitical tensions. ### Commodity market developments (recent) - Between August 2023 and February 2024: - Oil monthly average in February 2024: $80.70; oil prices decreased by 4.2 percent over that period. - TTF prices in Europe fell 24.4 percent to $8.10 per MMBtu in February 2024. - IMF base metals price index rose 4.7 percent; iron ore up 14.9 percent; uranium up 75.3 percent. - IMF food and beverages price index gained 6.0 percent; cereals down 7.2 percent; vegetable oils down 10.9 percent. - Futures: oil futures suggest average $78.60 per barrel in 2024 and $67.50 in 2029. --- *Italic: Source — World Economic Outlook, International Monetary Fund, April 2024 (selected Preface, Foreword, Chapters 1–4, Boxes, Special Feature, and Statistical Appendix excerpts as provided).* ### Preface ### Preface ### Report structure and major themes - The World Economic Outlook includes: - Executive Summary - Chapter 1. Global Prospects and Policies — "Disinflation amid Economic Resilience"; The Outlook; Risks to the Outlook; Globally Consistent Risk Assessment; Policies: From Fighting Inflation to Restocking Fiscal Arsenals; Commodity Special Feature: Market Developments and the Power of Prices. - Chapter 2. Feeling the Pinch? Tracing the Effects of Monetary Policy through Housing Markets — Introduction; Monetary Tightening and Real Estate; The Housing Channels of Monetary Policy Transmission; Housing Channels Vary Significantly across Countries; Housing Channels May Have Weakened in Many Countries; Policy Implications. - Chapter 3. Slowdown in Global Medium-Term Growth: What Will It Take to Turn the Tide? — Introduction; Insights from Medium-Term Forecasts; How Did We Get Here?; Where Is Growth Heading?; Conclusions and Policy Recommendations. - Chapter 4. Trading Places: Real Spillovers from G20 Emerging Markets — Introduction; G20 Emerging Markets in the Global Economy; Aggregate Spillovers in the Short Term; Spillovers from Trade and Global Value Chains; Can the Other G20 Emerging Markets Support Global Growth?; Conclusions and Policy Implications. - Statistical Appendix, Tables, Figures, Boxes, and Online Tables covering detailed projections, assumptions, classifications, and data documentation. ### Key numerical assumptions underlying the WEO projections - Real effective exchange rates are assumed to remain constant at their average levels during January 30, 2024–February 27, 2024, except for currencies participating in the European exchange rate mechanism II, which are assumed to have remained constant in nominal terms relative to the euro. - Established policies of national authorities are assumed to be maintained (see Box A1 in the Statistical Appendix for specific fiscal and monetary policy assumptions for selected economies). - Average price of oil assumptions: - $78.61 a barrel in 2024 - $73.68 a barrel in 2025 - Three-month government bond yield assumptions: - United States: 5.2 percent in 2024 and 4.1 percent in 2025 - Euro area: 3.5 percent in 2024 and 2.6 percent in 2025 - Japan: 0.0 percent in 2024 and 0.1 percent in 2025 - 10-year government bond yield assumptions: - United States: 4.1 percent in 2024 and 3.7 percent in 2025 - Euro area: 2.5 percent in 2024 and 2.6 percent in 2025 - Japan: [value appears in source continuation beyond supplied excerpt] *Source: Preface, World Economic Outlook — April 2024 (text - Preface).* ### 1.0 percent in 2024 and 1.1 percent in 2025. These are, of course, working hypotheses rather than forecasts, ### ASSUMPTIONS AND CONVENTIONS ### Summary of key assumptions and data conventions - Growth working hypotheses: 1.0 percent in 2024 and 1.1 percent in 2025. These are working hypotheses rather than forecasts. - Estimates and projections are based on statistical information available through April 1, 2024. - Data refer to calendar years, except for a few countries that use fiscal years (see Table F in the Statistical Appendix for exceptional reporting periods). - For some countries, figures for 2023 and earlier are based on estimates rather than actual outturns (see Table G in the Statistical Appendix for latest actual outturns). - Composite country-group calculations are based on 90 percent or more of the weighted group data unless noted otherwise. - Minor discrepancies between sums of constituent figures and totals reflect rounding. ### Notational conventions used throughout the WEO - . . . indicates that data are not available or not applicable. - – between years or months (for example, 2023–24 or January–June) indicates the years or months covered, including the beginning and ending years or months. - / between years or months (for example, 2023/24) indicates a fiscal or financial year. - “Billion” means a thousand million; “trillion” means a thousand billion. - “Basis points” refers to hundredths of 1 percentage point (for example, 25 basis points are equivalent to ¼ of 1 percentage point). - Tables and figures listing their source as “IMF staff calculations” or “IMF staff estimates” draw on data from the WEO database. - When countries are not listed alphabetically, they are ordered on the basis of economic size. - Boundaries, colors, denominations, and any other information shown on maps do not imply any judgment on the legal status of any territory or endorsement or acceptance of such boundaries. - The terms “country” and “economy” may cover some territorial entities that are not states but for which statistical data are maintained on a separate and independent basis. ### What is new in this publication - Ecuador’s fiscal sector projections are excluded from publication for 2024–29 because of ongoing program discussions. - Vietnam has been removed from the Low-Income Developing Countries (LIDCs) group and added to the Emerging Market and Middle-Income Economies (EMMIEs) group. - For West Bank and Gaza, data for 2022–23 previously excluded from publication pending methodological adjustments to statistical series are now included. Projections for 2024–29 are excluded from publication on account of the unusually high degree of uncertainty. ### Data quality, revisions, and availability - The estimates and projections use historical data compiled by IMF country desk officers and IMF staff estimates where complete information is unavailable; historical series are sometimes smoothed using splicing and other techniques. - WEO data can differ from other sources with official data, including the IMF’s International Financial Statistics. - WEO data and metadata are provided “as is” and “as available.” Corrections and revisions discovered after publication are incorporated into the electronic editions available from the IMF eLibrary and IMF website; all substantive changes are listed in detail in the online tables of contents. - Multiple digital editions of the WEO, including ePub, enhanced PDF, and HTML, are available on the IMF eLibrary. ### Key analytic context and headline projections cited in the Preface - Global growth bottomed out at the end of 2022 at 2.3 percent, shortly after median headline inflation peaked at 9.4 percent. - Latest projections: growth for 2024 and 2025 will hold steady around 3.2 percent, with median headline inflation declining from 2.8 percent at the end of 2024 to 2.4 percent at the end of 2025. - Noted risks and themes: - Services inflation remains high and could derail disinflation. - The United States’ exceptional performance is driven in part by a fiscal stance described as out of line with long-term fiscal sustainability. - China’s economy is affected by an enduring downturn in its property sector, with risks to public debt dynamics and domestic demand. - Low-income developing countries show widening divergence: growth revised downward and inflation revised up; scarring estimates for these countries have been revised up. - Real interest rates have increased as inflation recedes, worsening sovereign debt dynamics for highly indebted emerging markets; rebuilding fiscal buffers is urged. - Medium-term growth prospects are historically weak, with lower total factor productivity growth and increased misallocation of capital and labor. - Artificial intelligence (AI) may deliver productivity gains but poses disruption risks requiring investments in digital infrastructure and human capital and global coordination. - Geoeconomic fragmentation and rising trade-restrictive and industrial policy measures since 2019 harm medium-term prospects and global cooperation. - Large global investments are required for a green and climate-resilient future; emissions remain on the rise despite declining emissions intensity of growth. *Source: World Economic Outlook (WEO), IMF staff analysis and conventions, April 2024.* ### FOREWORD ### FOREWORD ### Disinflation amid economic resilience - Economic activity was "surprisingly resilient" through the global disinflation of 2022–23. - Growth in employment and incomes held steady, supported by greater-than-expected government spending and household consumption, and a supply-side expansion including an "unanticipated boost to labor force participation." - Households in major advanced economies drew on "substantial savings accumulated during the pandemic." - Changes in mortgage and housing markets over the prepandemic decade of low interest rates moderated the near-term impact of policy rate hikes. - As inflation converges toward target levels and central banks pivot toward policy easing in many economies, "a tightening of fiscal policies aimed at curbing high government debt, with higher taxes and lower government spending, is expected to weigh on growth." ### Global growth and inflation projections - Global growth was estimated at "3.2 percent in 2023" and is projected to continue at "the same pace in 2024 and 2025." - The forecast for 2024 is revised up by "0.1 percentage point" from the January 2024 WEO Update and by "0.3 percentage point" from the October 2023 WEO. - Global headline inflation is expected to fall from "an annual average of 6.8 percent in 2023" to "5.9 percent in 2024" and "4.5 percent in 2025." - The latest forecast for global growth five years from now is "3.1 percent." - In late 2023, headline inflation for advanced economies was "2.3 percent on a quarter-over-quarter annualized basis" (down from "9.5 percent" peak in 2022:Q2). - For emerging market and developing economies, headline inflation was "9.9 percent in the last quarter of 2023" (down from "13.7 percent" peak in 2022:Q1); for the median emerging market and developing economy, inflation declined to "3.9 percent." ### Sources of the resilience: demand and supply factors - During 2022 and 2023, global real GDP rose by a cumulative "6.7 percent"—"0.8 percentage point higher than the forecasts made at the time of the October 2022 World Economic Outlook." - Aggregate demand support included stronger-than-expected private consumption and larger-than-expected government spending; the overall budgetary stance was "more expansionary than expected, on average." - Additional budgetary support relative to October 2022 WEO forecasts was estimated at "2 percent of GDP in the United States" and "0.2 percent of GDP in the euro area"; in China the fiscal stance was "mildly tighter than expected, by 0.7 percent of GDP." - A greater-than-expected rise in the labor force, including faster growth in the foreign-born than the domestic-born labor force since 2021, and higher labor force participation rates supported activity and disinflation in many economies. - Greater-than-expected additions to the stock of physical capital and a resolution of pandemic-era supply-chain problems (with lower delivery times and transportation costs) further bolstered supply in most regions. - After attacks on commercial shipping in the Red Sea—through which "11 percent of global trade flows"—global transportation costs increased due to rerouting but remained well below 2021–22 levels and have recently declined. - The price of energy "fell faster than expected from its peak," aided by increased non-OPEC oil production and increased natural gas output, most notably in the United States; rising exports of Russian oil and Russia’s maritime arrangements also added to world energy supply. ### Inflation dynamics and expectations - The fall in headline inflation since 2022 reflects fading relative price shocks (notably energy) and lower core inflation. - Monetary tightening by major central banks during 2022–23 likely contributed to lowering energy prices via synchronized policy and reduced world energy demand. - Core inflation declined due to fading pass-through from past shocks and easing labor market pressures. - Near-term inflation expectations have declined toward target levels in both advanced economies and emerging market and developing economies; measures of financial-market-based inflation expectations have recently shown signs of a pickup in the US. - Longer-term inflation expectations have remained anchored. - Labor markets remain tight, especially in the United States, but the ratio of vacancies to unemployed has declined amid rising unemployment rates, suggesting easing across several economies. - Nominal wage growth has generally remained contained in advanced economies since 2022; real wages are "now close to or slightly below the level they were on before the pandemic" in these economies. - Wages at the bottom of the distribution have risen faster than the average since the start of the pandemic, compressing the distribution. ### Risks to the global outlook - Downside risks: - New price spikes from geopolitical tensions (including the war in Ukraine and the conflict in Gaza and Israel) could raise interest rate expectations and reduce asset prices. - Persistent core inflation where labor markets are still tight could raise rate expectations. - Divergent disinflation speeds across major economies could cause currency movements that pressure financial sectors. - High interest rates could have greater cooling effects as fixed-rate mortgages reset and households with high debt face stress. - In China, growth could falter without a comprehensive response to the troubled property sector, hurting trading partners. - A disruptive turn to tax hikes and spending cuts amid high government debt could weaken activity, erode confidence, and sap support for climate and reform spending. - Geoeconomic fragmentation could intensify, raising barriers to goods, capital, and people and implying a supply-side slowdown. - Upside risks: - Looser fiscal policy than assumed could raise activity in the short term but risk costlier adjustments later. - Inflation could fall faster than expected amid further gains in labor force participation, allowing earlier central bank easing. - Artificial intelligence and stronger-than-anticipated structural reforms could spur productivity. ### Policy guidance and multilateral priorities - Near-term priority for central banks: ensure inflation "touches down smoothly, by neither easing policies prematurely nor delaying too long and causing target undershoots." - As central banks ease, a renewed focus on implementing medium-term fiscal consolidation is recommended to rebuild fiscal room, enable priority investments, and ensure debt sustainability. - Cross-country differences necessitate tailored policy responses. - Intensifying supply-enhancing reforms would facilitate inflation and debt reduction, enable higher growth toward pre‑pandemic averages, and accelerate convergence for middle- and lower-income countries. - Multilateral cooperation is needed to limit costs and risks of geoeconomic fragmentation and climate change, speed the transition to green energy, and facilitate debt restructuring. - On green investment and fossil fuel subsidies: "Cutting harmful fossil fuel subsidies can help create the necessary fiscal room for further green investments." Emerging market and developing economies "need to massively increase their green investment growth and reduce their fossil fuel investment," requiring technology transfer by advanced economies and China, and "substantial financing, much of it from the private sector, but some of it concessional." - "There is little hope for progress outside multilateral frameworks and cooperation." *International Monetary Fund | April 2024* ### CHAPTER 1 gLObaL PROSPECTS aND POLICIES ### CHAPTER 1 gLObaL PROSPECTS aND POLICIES ### Labor Markets and Inflation Drivers - IMF staff estimates of the output gap in 2023: United States +0.7 percent; euro area –0.3 percent; United Kingdom –0.3 percent. - Main upward pressures on underlying inflation: labor market tightness, pass-through effects, longer-term expectations, and headline inflation shocks (decomposition referenced in Figure 1.8). - Excess household savings accumulated during the pandemic have declined in major advanced economies since 2022; estimates based on a linear trend show a less pronounced drop for some economies. - Labor market indicators show cooling: unemployment rates, vacancy-to-unemployment ratios, and real wages trends are presented for multiple economies (see Figure 1.7 and Figure 1.8 referenced). ### Interest Rates: Recent Tightening and Prospects - Major central banks raised policy interest rates to levels estimated as restrictive, contributing to higher mortgage costs, tighter credit availability, rising corporate bankruptcies, and subdued business and residential investment in several economies. - Country differences in timing and magnitude of real rate increases: some central banks (European Central Bank, Federal Reserve) raised nominal rates after inflation expectations rose, resulting initially in lower real rates; Bank of Japan kept policy rates near zero and saw a steady decline in real interest rates; central banks in Brazil, Chile, and several other EMDEs raised rates relatively quickly, producing earlier increases in real rates. - Monetary policy projections (selected advanced economies, fourth quarter of 2024): - Federal Reserve policy rate projected to decline from about 5.4 percent to 4.6 percent. - Bank of England projected to reduce its policy rate from about 5.3 percent to 4.8 percent. - European Central Bank projected to reduce its short-term rate from about 4.0 percent to 3.3 percent. - Japan: policy rates projected to rise gradually. - As inflation moves toward targets, market expectations of lower policy rates have contributed to declines in long-term borrowing rates, rising equity markets, and an easing in overall global financial conditions since last October, though funding remains more expensive than before the pandemic. ### Elevated Debt Burdens and Fiscal Policy - Debt-to-GDP ratios remain elevated after sharp increases during the pandemic; large budget deficits continue to raise the debt burden. - Interest payments on debt have increased as a share of government revenues, crowding out growth-enhancing budgetary investments. - Low-income countries: interest payments on debt estimated to average 14.3 percent of general government revenues in 2024, about double the level 15 years ago. - Fiscal policy projections and expected adjustments: - Advanced-economy fiscal stance expected to tighten in 2024 and to a lesser extent in 2025–26. - Structural fiscal-balance-to-GDP ratio projected to rise by 1.9 percentage points in the United States in 2024 and by 0.8 percentage point in the euro area in 2024. - Emerging market and developing economies projected to have, on average, a broadly neutral fiscal stance in 2024, with a tightening of about 0.2 percentage point projected for 2025. - The expected fiscal tightening is anticipated to weigh on near-term economic activity. ### Commodity Price and Other Baseline Assumptions - Commodity price projections for 2024 (averages and changes as presented): - Prices of fuel commodities projected to fall in 2024 by, on average, 9.7 percent. - Oil prices projected to fall by about 2.5 percent in 2024. - Coal prices projected to decline by 25.1 percent in 2024. - Natural gas prices projected to decline by 32.6 percent in 2024. - Base metals prices expected to fall by 1.8 percent in 2024. - Food commodity prices predicted to decline by 2.2 percent in 2024. - Nonfuel commodity prices: forecast broadly stable in 2024. - Real effective exchange rates are assumed to remain constant at levels prevailing during January 30, 2024—February 27, 2024. ### Growth and Inflation Outlook (Key Projections and Revisions) - Global growth: - 2023: 3.2 percent (estimate). - 2024: 3.2 percent (projection). - 2025: 3.2 percent (projection). - The 2024 projection is revised up by 0.1 percentage point from the January 2024 WEO Update and by 0.3 percentage point from the October 2023 WEO. - World growth projections remain below the historical (2000–19) annual average of 3.8 percent. - Advanced economies growth: - 2023: 1.6 percent. - 2024: 1.7 percent. - 2025: 1.8 percent. - Selected country projections: - United States: 2023: 2.5 percent; 2024: 2.7 percent; 2025: 1.9 percent. The 2024 projection is revised up by 0.6 percentage point since the January 2024 WEO Update. - Euro area: 2023: 0.4 percent; 2024: 0.8 percent; 2025: 1.5 percent. - Japan: 2023: 1.9 percent; 2024: 0.9 percent; 2025: 1.0 percent. - United Kingdom: 2023: 0.1 percent; 2024: 0.5 percent; 2025: 1.5 percent. - China: 2023: 5.2 percent; 2024: 4.6 percent; 2025: 4.1 percent. - India (fiscal year basis): 2023: 7.8 percent; 2024: 6.8 percent; 2025: 6.5 percent. - Inflation (World consumer prices): - 2023: 6.8 percent. - 2024: 5.9 percent. - 2025: 4.5 percent. - Inflation by country group: - Advanced economies: 2023: 4.6 percent; 2024: 2.6 percent; 2025: 2.0 percent. - Emerging Market and Developing Economies: 2023: 8.3 percent; 2024: 8.3 percent; 2025: 6.2 percent. - Trade and regional growth: - World trade volume (goods and services): 2023: 0.3 percent; 2024: 3.0 percent; 2025: 3.3 percent. - Emerging Market and Developing Economies (aggregate): 2023: 4.3 percent; 2024: 4.2 percent; 2025: 4.2 percent. - Emerging and Developing Asia: 2023: 5.6 percent; 2024: 5.2 percent; 2025: 4.9 percent. ### Risks, Financial Conditions, and Near-Term Dynamics - Despite restrictive policy rates, a sharp global economic downturn has not materialized owing to: - Timing of nominal rate increases relative to inflation expectations, which initially lowered real rates in some economies. - Use of pandemic-era savings by households in major advanced economies to cushion the impact of higher borrowing costs. - Greater prevalence of fixed-rate mortgages and longer maturities moderating immediate pass-through of policy rate hikes to household consumption in several economies. - Cooling effects of high policy rates are intensifying as fixed-rate mortgages reset, pandemic savings decline, and real policy rates rise where nominal rates have not changed. - Sovereign spreads in emerging market and developing economies have fallen from July 2022 peaks toward prepandemic levels, and more governments are accessing international debt markets in 2024. *Source: CHAPTER 1 gLObaL PROSPECTS aND POLICIES, text - CHAPTER 1 gLObaL PROSPECTS aND POLICIES (PDF).* ### CHAPTER 1 gLObaL PROSPECTS aND POLICIES ### CHAPTER 1 gLObaL PROSPECTS aND POLICIES ### Overview of World Economic Projections - World output projections (Q4 over Q4): 2023 = 3.2, 2024 = 3.2, 2025 = 3.1. - Advanced Economies: 2023 = 1.6, 2024 = 1.9, 2025 = 1.7. - United States: 2023 = 3.1, 2024 = 2.1, 2025 = 1.8. - Euro Area: 2023 = 0.1, 2024 = 1.4, 2025 = 1.4. - Germany: 2023 = –0.2, 2024 = 0.7, 2025 = 1.8. (Revised downward by 0.3 percentage point for 2024 and 2025.) - France: 2023 = 0.7, 2024 = 1.1, 2025 = 1.5. - Italy: 2023 = 0.6, 2024 = 0.7, 2025 = 0.6. - Spain: 2023 = 2.0, 2024 = 1.9, 2025 = 2.1. - Japan: 2023 = 1.3, 2024 = 1.7, 2025 = 0.5. - United Kingdom: 2023 = –0.2, 2024 = 1.5, 2025 = 1.3. - Emerging Market and Developing Economies: 2023 = 4.5, 2024 = 4.3, 2025 = 4.1. - Commodity prices (US dollars): Oil — 2023 = –4.4, 2024 = –6.0, 2025 = –5.5 (percent change as presented). - Oil price levels: average price in 2023 = $80.59 per barrel; assumed price = $78.61 in 2024 and $73.68 in 2025. ### Growth Forecast for Emerging Market and Developing Economies - Aggregate expectation: growth stable at 4.2 percent in 2024 and 2025. - Low-income developing countries: 2023 = 4.0 percent; 2024 = 4.7 percent; 2025 = 5.2 percent. - Emerging and developing Asia: - 2023 = 5.6 percent (estimated), 2024 = 5.2 percent, 2025 = 4.9 percent. - China: 2023 = 5.2 percent, 2024 = 4.6 percent, 2025 = 4.1 percent. - India: projected to remain strong at 6.8 percent in 2024 and 6.5 percent in 2025. - Emerging and developing Europe: - 2023 = 3.2 percent, 2024 = 3.1 percent, 2025 = 2.8 percent. - Russia: 2024 = 3.2 percent, 2025 = 1.8 percent. - Türkiye: 2024 = 3.1 percent, 2025 = 3.2 percent. - Latin America and the Caribbean: - 2023 = 2.3 percent (estimated), 2024 = 2.0 percent, 2025 = 2.5 percent. - Brazil: 2024 = 2.2 percent. - Mexico: 2024 = 2.4 percent, 2025 = 1.4 percent. - Middle East and Central Asia: 2023 = 2.0 percent (estimated), 2024 = 2.8 percent, 2025 = 4.2 percent. - Sub-Saharan Africa: 2023 = 3.4 percent (estimated), 2024 = 3.8 percent, 2025 = 4.0 percent. ### Inflation Outlook - Global headline inflation: 2023 annual average = 6.8 percent; 2024 = 5.9 percent; 2025 = 4.5 percent. - Advanced economies: inflation expected to fall by 2.0 percentage points in 2024; average in 2025 = 2.0 percent. - Emerging market and developing economies: return to pre-pandemic average near 5.0 percent expected later than advanced economies. - Regional inflation range (2024–25 context): - Emerging and developing Asia: 2.4 percent (reflecting subdued inflation in China and Thailand). - Emerging and developing Europe: 18.8 percent (reflecting elevated inflation in Türkiye). - Global inflation forecast revision: upward by 0.1 percentage point in 2024 from January 2024 projections. - This reflects an upside revision of 0.2 percentage point in emerging market and developing economies. - Core inflation: expected to fall by 1.2 percentage points in 2024 after contracting by 0.2 percentage point in 2023. - Inflation among economies with targets: median deviation from target by 2024:Q3 = 0.5 percentage point above target; for advanced economies median gap = 0.3 percentage point by 2024:Q3. Most economies expected within 0.25 percentage point of targets by 2025:Q2. ### World Trade and Current Account Dynamics - World trade growth: 2024 = 3.0 percent, 2025 = 3.3 percent. - Revisions: a 0.3 percentage point decrease for 2024 and 2025 compared with January 2024 projections. - Medium-term trade growth: 3.2 percent in 2029 (below the 2000–19 annual average of 4.9 percent). - Projected ratio of total world trade to GDP (current dollars): averages 57 percent over the next five years. - Trade-pattern shifts: growth in trade between geopolitical blocs has declined significantly since February 2022 relative to within-bloc trade; about 3,200 new trade restrictions in 2022 and about 3,000 in 2023 (Global Trade Alert data) versus about 1,100 in 2019. - Global current account balances: expected to continue narrowing in 2024 following a significant increase in 2022. Creditor and debtor stock positions increased in 2023 with valuation losses in debtor economies and gains in creditor economies more than offsetting narrower current account balances. ### Medium-Term Growth Outlook and Drivers - Global growth forecast for 2029 = 3.1 percent (unchanged since October 2023 WEO). - Comparison points: - Medium-term projection before the pandemic (January 2020 WEO Update) = 3.6 percent. - Medium-term projection before global financial crisis (April 2008 WEO) = 4.9 percent. - Historical (2000–19) annual average actual global growth = 3.8 percent. - Decline in medium-term prospects largely reflects lower prospective growth in GDP per person: - GDP per person medium-term forecast fell from 3.9 percent (before the global financial crisis) to 2.1 percent in latest projections. - Key contributing factors to slower medium-term growth: - Lower growth in total factor productivity. - Declining labor force participation amid population aging. - Weaker business investment. - Persistent structural frictions hindering resource reallocation to more productive firms. - Dimmer prospects for growth in China and other large emerging market economies. - Geo-economic fragmentation reducing international flows and scope for efficiency gains. ### Risks to the Outlook (Broadly Balanced) - Overall risk distribution: broadly balanced around baseline for global growth; risks diminished since October 2023. - Downside risks highlighted: - New commodity price spikes amid regional conflicts: - Escalation in Gaza and Israel, continued attacks in the Red Sea, and the ongoing war in Ukraine could trigger supply shocks raising food, energy, and transportation costs. - Such shocks could complicate disinflation and delay central bank easing, harming global growth and disproportionately affecting lower-income countries where food and energy shares of expenditure are large. - Persistent inflation and financial stress: - Slower-than-expected decline in core inflation in major economies (for example, due to labor market tightness or renewed tensions) could sustain elevated policy rates and financial stress. - Geopolitical risk and oil price relationship illustrated by the Geopolitical Risk Index and Brent crude oil price (historical series shown in Figure 1.20). *Source: IMF staff estimates, World Economic Outlook, April 2024.* ### CHAPTER 1 gLObaL PROSPECTS aND POLICIES ### CHAPTER 1 gLObaL PROSPECTS aND POLICIES ### Near-term downside risks and channels - Financial tightening and real effects: - Further monetary tightening or re‑pricing of interest rate expectations could trigger a fall in asset prices and tighter global financial conditions, strengthen the US dollar, and reduce global growth. - The cooling effects of past monetary tightening may still be coming, especially where fixed‑rate mortgages are resetting and household debt is high, increasing defaults in sectors including commercial real estate and firms and raising risks to financial stability. - Flight‑to‑safety capital flows could tighten global financial conditions and amplify growth losses. - China’s property sector and domestic demand: - In the absence of a comprehensive restructuring policy package for the troubled property sector in China, a larger and more prolonged drop in real estate investment could occur, with expectations of future house prices declining, reduced housing demand, and weakened household confidence and spending. - Unintended fiscal tightening from local government financing constraints could amplify the impact. - In such a scenario, disinflationary pressures could intensify, resulting in sustained low inflation or deflation, and spillovers to China’s trading partners are estimated to be, on balance, negative. - Policy steps that could mitigate costs include accelerating the exit of nonviable property developers, promoting completion of housing projects, resolving local government debt risks, monetary policy easing through lower interest rates, and expansionary fiscal measures including funding of unfinished housing and support to vulnerable households. - Disruptive fiscal adjustment and debt distress: - Excessively sharp fiscal consolidation (tax hikes and spending cuts beyond current plans) could lead to slower-than-expected growth and reduced reform momentum. - Countries lacking credible medium‑term consolidation plans could face adverse market reactions or increased risks of debt distress that force harsh adjustment. - The share of low‑income countries in or at high risk of debt distress in 2024 is 54 percent; the share of emerging markets in or at high risk of debt distress in 2024 is 16 percent. - Erosion of trust and reform momentum: - Confidence in government, legislative bodies, and political parties is below 50 percent across broad income groups by some measures, which could sap support for structural reforms and complicate adoption of technological advances, revenue efforts, and social cohesion. - Geoeconomic fragmentation: - Intensifying separation of the world economy into blocs could generate more restrictions on trade and cross‑border flows of capital, technology, and workers, reduce portfolio and foreign direct investment flows, slow innovation and technology adoption, constrain commodity flows, cause large output losses, and increase commodity price volatility. - Moves to raise barriers to international flow of workers could reverse recent supply‑side gains, exacerbate labor market tightness and skill shortages, and raise inflationary pressures. Tariff increases could trigger retaliatory responses and raise costs. ### Upside scenarios and beneficial shocks - Short‑term fiscal boosts around elections: - Many countries are expected to elect national governments in 2024; policymakers may postpone fiscal adjustment or commit to new expansionary measures that could boost activity in the near term, though they risk adding to inflationary pressures and higher interest rates and could lead to disruptive subsequent adjustments. - Faster easing of inflation and supply‑side surprises: - Downside surprises to core inflation from faster-than-expected fading of pass‑through effects and easing of global supply constraints could allow central banks to bring forward policy easing, reducing borrowing costs and raising consumer confidence. - Artificial intelligence (AI) productivity gains: - Recent advances (large language models and generative pretrained transformers) could boost investment and, over the medium term, raise worker productivity and incomes while also causing job displacement and inequality. - AI could affect about 60 percent of workers in advanced economies (with about half of those exposed achieving higher productivity and incomes and half seeing lower demand for their labor and lower wages). - AI could affect about 40 percent of jobs in emerging market economies and 26 percent of jobs in low‑income countries, implying smaller near‑term labor market disruption and less scope for related productivity improvements in those groups. - Structural reform momentum: - Faster implementation of macrostructural reforms (increasing labor participation, reducing resource misallocation, improving allocation of talent) could boost productivity and medium‑term growth beyond baseline forecasts and help heal pandemic scarring. - In EMDEs with constrained policy environments, faster progress on supply‑enhancing reforms (governance, business regulation, external sector policies) could spur domestic and foreign investment and growth. Narrowing gender gaps in labor market participation would amplify reform returns. ### Global risk assessment and probabilistic outlook - The estimated probability that global growth in 2024 will fall below 2.0 percent is about 10 percent, down from an estimated 15 percent at the time of the October 2023 WEO. - For 2025, the probability of global growth falling below 2.0 percent is also about 10 percent. - The estimated probability of a contraction in global per capita real GDP in 2024 is below 5 percent. - The probability of global growth’s exceeding the 3.8 percent historical average during 2000–19 is slightly above 20 percent for 2024. - On inflation, the probability that core inflation in 2024 will be higher than in 2023, instead of declining to 4.9 percent in 2024 from 6.2 percent in 2023, is assessed at less than 10 percent. ### Policy guidance and recommendations - Central banks: - Ensure inflation comes down smoothly; neither ease prematurely nor delay too long. - Where core inflation persists above target‑consistent levels, higher real interest rates may be necessary. - Where near‑term inflation expectations and underlying gauges are clearly declining toward target, avoid delaying nominal policy rate cuts excessively to prevent unintended policy tightening that raises real rates and risks economic weakness. - In emerging market economies that tightened early and are at lower restrictive levels, proceed cautiously guided by data on inflation expectations, currency movements, and wage and price pressures. - Fiscal policy and rebuilding buffers: - Renewed focus on medium‑term fiscal consolidation is needed to rebuild room for budgetary maneuver and priority investments and to ensure debt sustainability. - Intensifying supply‑enhancing reforms would facilitate both inflation and debt reduction, increase growth toward higher prepandemic averages, and accelerate convergence toward higher income levels. - Financial sector and macroprudential measures: - Strengthen supervision (including implementation of Basel III) to anticipate banking sector stress given still‑high borrowing costs in numerous economies. - Recalibrate macroprudential policies where necessary in response to a fast‑evolving housing market. - Deploy liquidity support tools promptly and forcefully when market strains emerge, while mitigating moral hazard. - In countries with shallow foreign exchange markets and large foreign‑currency debts, consider foreign exchange intervention or capital flow management measures while keeping monetary and fiscal policy appropriate; use macroprudential policies to reduce vulnerabilities from foreign‑currency‑denominated debt. - Multilateral cooperation: - Coordinate to limit costs and risks of geoeconomic fragmentation and climate change, accelerate transition to green energy, and encourage debt restructuring. - Use of IMF frameworks: - The IMF’s Integrated Policy Framework provides guidance on appropriate policy responses depending on country circumstances, particularly concerning exchange rate flexibility, policy rates, and liquidity support. *International Monetary Fund | April 2024* ### CHAPTER 1 gLObaL PROSPECTS aND POLICIES ### CHAPTER 1 gLObaL PROSPECTS aND POLICIES ### Rebuilding Room for Budgetary Maneuver and Ensuring Debt Sustainability - Context and challenge: - Major central banks are expected to ease monetary policy this year, and economies are in a better position to absorb the economic effects of fiscal tightening. - The size of the fiscal adjustment needed to ensure government debt sustainability is large in numerous cases. - Comparison presented: projected rise in the general government primary fiscal balance between 2023 and 2029 versus the increase needed to stabilize the general government debt-to-GDP ratio in 2029 and the additional adjustment needed to reduce debt to its 2019 level in 2029. - Note on interest-rate measures: adjustments to stabilize debt-to-GDP ratios are computed using the effective rate (government’s average interest rate on its total current debt stock); the marginal interest rate denotes the real interest rate based on the currently prevailing rate at the 10-year bond maturity (as of March 31, 2024). - Country-specific notes: China’s deficit and public debt numbers cover a narrower perimeter of the general government than IMF staff’s Article IV estimates; Korea’s policy lending is not included in the calculation of needed fiscal adjustment. - Key findings: - The currently foreseen adjustment over 2023–29 is sufficient to stabilize the debt-to-GDP ratio in 2029 in most—although not all—cases. - The projected adjustment is generally not sufficient to return debt to 2019 levels. - The adjustment needed to achieve debt reduction to 2019 levels is even more challenging when assessed at the marginal interest rates that currently apply to newly issued debt. - With elections in a number of countries in 2024, ensuring that any new tax cuts or spending increases are funded and do not expand budget deficits is necessary to preserve the envisaged fiscal adjustment path. - Policy recommendations: - Calibrating the pace of adjustment: - Fiscal adjustment should be gradual and sustained, where possible, given its generally negative near-term effects on economic activity. - Avoid abrupt adjustment to prevent a negative cycle of slowing activity and rising debt ratios and to preserve political support for fiscal reforms. - Front-loaded adjustment may be necessary in economies that have lost market access to reduce the likelihood of a debt crisis. - For countries with elevated inflation, fiscal consolidation can help reduce aggregate demand and reinforce credibility of disinflation strategies. - Complementary measures: supply-enhancing structural reforms, protecting targeted support for the most vulnerable, and priority investments during adjustment to mitigate near-term impacts and support medium-term debt reduction. - Building credibility with well-specified plans and a strong institutional framework: - Commit to measures sufficient to meet medium-term targets based on realistic assumptions about short-term growth effects of consolidation, interest rates, and budgetary yields. - Phase out untargeted fiscal measures that blunt price signals as energy prices return to prepandemic levels. - Back medium-term plans with binding legislation, fiscal frameworks, and clear contingencies for responses to unexpected growth and interest-rate movements. - Evidence: sovereign debt ratings reward reductions in debt-to-GDP ratios but place a high premium on institutional quality (see related Figure 1.25). - Addressing debt distress: - For countries in debt distress, orderly debt restructuring may be necessary. - Progress noted: G20 Common Framework has started to deliver with faster coordination across successive cases; the Global Sovereign Debt Roundtable aids more timely and predictable restructurings. - Continuing to build on progress and improving creditor coordination efficiency—especially for cases outside the Common Framework—is important. ### Fostering Faster Productivity Growth - Core messages: - Structural reforms, when targeted and carefully sequenced, can support productivity growth and reverse declining medium-term growth prospects. - Prioritize reforms that relax the most binding constraints on economic activity to generate output and productivity gains, even in the short term. - Address persistent misallocation of resources; narrowing gender gaps to correct misallocation of women’s talents and abilities would further enhance aggregate productivity. - Suggested reform areas: - Strengthen governance, reduce excessive business regulation and trade restrictions, and improve access to foreign capital. - Bundle reforms and sequence complementary reforms (for example, labor market and credit market reforms) to front-load gains. - Harnessing artificial intelligence requires regulatory frameworks, foundational infrastructure, and digital skills training; complementary reforms to support and retrain displaced workers are needed. - Industrial policies can be pursued when externalities or market failures are well established, but should avoid protectionist provisions and be consistent with World Trade Organization (WTO) rules. ### Speeding the Green Transition and Building Climate Resilience - Gaps and needs: - Large global policy action gaps persist for reaching emissions reduction goals consistent with limiting global average temperature increases to 1.5–2.0°C above preindustrial levels. - A holistic set of mitigation instruments is needed: carbon pricing, public infrastructure investment in clean energy, sectoral policies, regulations, and reductions in fossil-fuel subsidies. - Carbon border-adjustment mechanisms and incentive programs for green investments can speed transition but must be consistent with WTO rules. - Fiscal incentives are needed to shift to clean energy sources. - Risks and complementary actions: - Energy security risks if scaling back fossil-fuel investment is not matched by increases in clean energy supplies. - Investments in climate adaptation activities and infrastructure are especially needed for regions most vulnerable to climate shocks. - Enhance climate-risk-monitoring systems, risk management frameworks, safety nets, and insurance to boost climate resilience. - Mobilizing climate finance for adaptation and mitigation in low-income countries will require coordinated efforts by international organizations, private investors, country authorities, and donors. ### Strengthening Cross-Border Cooperation - Priorities for multilateral cooperation: - Maintain stable and transparent trade policies; avoid discriminatory policies that induce trade and investment distortions. - Establish intergovernmental dialogue or consultation frameworks for industrial policies to improve data sharing, identify cross-border impacts and unintended consequences, and develop international rules and norms over time. - Cooperation for orderly resolution of debt problems amid a complex creditor landscape. - International coordination to mitigate climate change effects and facilitate the green-energy transition, building on 2023 Conference of the Parties agreements. - Safeguard transportation of critical minerals, restore WTO dispute-settlement capacity, and ensure responsible use of disruptive technologies (for example, artificial intelligence) through upgraded domestic regulation and harmonized global principles. - Promote free flow of low-carbon technologies from advanced economies to emerging market and developing economies. ### Fragmentation Is Already Affecting International Trade (Box 1.1) - Evidence of fragmentation: - Analysis assigns countries to a hypothetical bloc (Australia, Canada, European Union, New Zealand, United States) and a hypothetical bloc (China, Russia, and countries siding with Russia during the March 2, 2022, UN General Assembly vote), with other countries considered nonaligned. - Comparison periods: after Russia’s invasion (2022:Q2 to 2023:Q3) versus five years prior to the invasion (2017:Q1 to 2022:Q1). - Key findings: - Growth in goods trade between the two blocs has been significantly weaker since the start of the war than growth in goods trade within blocs. - Total goods trade has slowed by about 2.4 percentage points more between countries not in the same bloc than among those in the same bloc. - Strategic sectors (including Harmonized System two-digit chapters: 28, 29, 30, 38, 84, 85, 87, 88, 90, and 93) show trade slowed by about 4 percentage points more among countries not in the same bloc. - China–US links: China’s share of US goods imports fell by almost 8 percentage points (from 22 percent in 2017 to 14 percent in 2023). - Evidence of supply-chain reallocation away from China toward countries such as Mexico and Vietnam during 2017–2022. - Resulting dynamics: supply chains lengthening with possible losses in efficiency. - Implications: - Continued fragmentation and additional trade restrictions could cause efficiency losses from declines in specialization, smaller gains from economies of scale, and reduced competition. ### Confidence Bands and Risk Scenarios - Methodology: - Confidence bands derived from the IMF’s G20 Model following Andrle and Hunt (2020) and Andrle and others (2015). - Historical data on output, inflation, policy rates, and international commodity prices recover implied aggregate demand and supply shocks; shocks sampled nonparametrically and fed through the model to generate predictive distributions. - Shocks sampled uniformly, consistent with balanced risks; narrower distribution relative to October 2023 WEO because 2023 outturns are now known for most countries. - Summary of quantified risks and probabilities: - Risks to global growth are considered broadly balanced. - The risk that global growth will fall below 2 percent in 2024 is assessed at less than 10 percent, compared with 15 percent in October 2023. - The risk that core inflation will be higher in 2024 than in 2023 is now assessed at less than 10 percent, compared with 15 percent in October 2023. - Fan-chart results: - There is a 70 percent probability that global growth will be between 2.4 percent and 4.1 percent in 2024. - There is a 70 percent probability that global growth will be between 2.2 percent and 4.3 percent in 2025. - The distribution of forecast uncertainty is shown in 5 percentage point probability intervals (each shade of blue in the fan represents a 5 percentage point interval). *Source: IMF staff calculations and analysis in CHAPTER 1 gLObaL PROSPECTS aND POLICIES (text - CHAPTER 1 gLObaL PROSPECTS aND POLICIES).* ### Box 1.2. Risk Assessment Surrounding the World Economic Outlook’s Baseline Projections ### Box 1.2. Risk Assessment Surrounding the World Economic Outlook’s Baseline Projections ### Global inflation uncertainty and probabilities - There is a 70 percent probability that 2024 headline inflation will be about 1.3 percentage points higher or lower than currently projected (band smaller than the 1.8 percent band estimated in October). - The probability that headline inflation will be higher in 2024 than in 2023 is about 20 percent (compared with 25 percent in October). - The probability that core inflation will be higher in 2024 than in 2023 is assessed at less than 10 percent (compared with 15 percent in October). ### Scenarios analyzed (G20 model; monetary policy and automatic fiscal stabilizers respond endogenously unless stated) - Greater-than-expected healing from the pandemic (Healing scenario) - Assumes continued supply-side surprises over the medium term with greater normalization (healing) over 2024–26 than in the baseline, implying additional increases in potential output. - Country-specific improvements in total factor productivity help close the labor productivity gap by half relative to prepandemic forecasts: For the median G20 country, total factor productivity increases by about 2 percent over this period. - Labor force participation improves over the same period, fully closing the gap that opened through COVID-19, implying a 0.7 percentage point increase in labor force participation for the median G20 country. - Normalization is greater in emerging markets excluding China than in advanced economies. - Scenario does not assume supply-side improvement (relative to baseline) for China or the United States. - Fiscal policy (No consolidation scenario) - Current WEO projections: structural primary deficits in the median G20 country decreasing from about 1.5 percent of potential GDP in 2023 to zero by 2028, with most decrease in the first or second year. - Scenario assumption: fiscal tightening envisaged for 2024–25 does not take place; structural primary deficits remain at their 2023 levels in 2024 and increase further in 2025, implying some fiscal stimulus relative to the baseline in both years. - Stimulus greater in countries with larger expected fiscal withdrawal, such as the United States and the euro area in 2024 and Japan in 2025; no stimulus assumed for China. - Lack of fiscal consolidation generates an increase in global borrowing costs starting in 2025: - Advanced economies with debt levels above 100 percent of GDP experience increases in both term and sovereign premiums that peak at 100 basis points by 2026. - Emerging markets experience increases in both premiums that peak at 150 basis points by 2026. - A fiscal consolidation takes place in 2026–27; it is larger than in current projections to partly offset the effects of the initial expansion and higher premiums on debt accumulation. - Assumes fiscal expansions and contractions are implemented through changes in targeted and general transfers in equal parts and that automatic stabilizers are turned off. - Fiscal Impulse Relative to Baseline (Percent, year-over-year change in structural primary deficit in percent of potential GDP): - Advanced Economies: 2024 = 0.9; 2025 = 0.8; 2026 = –2.0; 2027 = –1.5 - Emerging Market and Developing Economies Excluding China: 2024 = 0.1; 2025 = 0.3; 2026 = –0.4; 2027 = –0.4 - (Source: IMF staff calculations.) - Deflation in China (China downside / deflation scenario) - Builds on October 2023 WEO downside for China but with greater deflationary pressures due to larger-than-realized economy-wide slack and excess capacity in goods sector and a steeper Phillips curve. - Core inflation in China declines relative to baseline by 1 percentage point in 2024 and 2 percentage points in 2025 and 2026, resulting in negative core inflation outturns in 2025–26. - China’s export price inflation decreases by 2 percentage points in 2024 and 4 percentage points in 2025 and 2026, respectively. - Fall in inflation is persistent but ultimately temporary: monetary and fiscal policy accommodation help the initial demand shock fade and inflation gradually converges back to baseline after 2026. - Geopolitical risk (Middle East escalation; shipping disruption) - Assumes oil prices are 15 percent higher and average container prices rise by 150 percent in 2024–25 (increase concentrated in Asia-to-Europe routes). - Oil prices and container costs return to baseline in 2026. - Divergence and global financial conditions (Greater-than-expected divergence among advanced economies) - US domestic demand increases by 1.5 percent in 2024 relative to current projections. - Domestic demand decreases by 0.5 percent in Japan and 1 percent in the euro area in 2024. - Monetary policy diverges: tighter in the US (policy rates 70 basis points higher than baseline in 2024), looser in the euro area, unchanged in Japan. - Sovereign premiums in emerging markets and developing countries excluding China increase by 150 basis points in 2024–25. - Corporate premiums increase in emerging market and advanced economies by 75 basis points over 2024–25. - Premiums return to long-term averages in 2026. ### Impact on world output and inflation (summary of scenario effects; deviations from baseline) - Presentation notes - Effects on GDP: percent deviations from baseline (levels) for 2024–27. - Effects on headline inflation: percentage point deviations from baseline for 2024–27. - Global aggregates shown; advanced economies shown by red squares; emerging market and developing economies by yellow diamonds in original figure. - Healing scenario - Generates a gradual and permanent increase in activity over the WEO horizon. - Global GDP increases cumulatively by 1.3 percent by 2027 relative to current projections. - Both advanced economies and emerging markets expand; increase larger in emerging markets excluding China. - Effect on inflation close to zero (offsetting forces: output increases less than potential → mild declines in core inflation; expansion pushes oil prices up → adds to headline inflation). - Fiscal scenario - Whipsaw-like movement in activity, inflation, and policy rates. - Global output initially increases relative to baseline, peaking at 0.5 percent in 2025. - Activity in advanced economies rises more than in emerging markets. - Global inflation about 30 basis points higher on average during 2024–25. - Monetary policy tighter (example: US policy rates increase by 100 basis points relative to baseline by 2025). - Reversal in global activity in 2026–27 as borrowing costs rise and fiscal policy withdraws; growth falls by about 1 percent relative to current projections in both 2026 and 2027 in advanced economies. - Global inflation about 60 basis points lower during 2026–27. - Monetary policy becomes accommodative; US policy rates 75 basis points lower than baseline by 2027. - China deflation scenario - Global GDP falls cumulatively by 0.5 percent relative to current projections by 2025. - Impact mostly direct on China’s GDP; activity spillovers to advanced economies and other emerging markets close to zero. - Lower Chinese export prices improve terms of trade for rest of world, lowering inflation and raising purchasing power outside China. - Inflation in advanced economies and emerging markets excluding China is 20 basis points lower on average during 2024–26 for both headline and core measures. - Policy rates outside China are lower; US rates 40 basis points lower than baseline by 2025. - Geopolitical risk scenario - Negative global supply shock. - Global headline inflation increases by close to 70 basis points in 2024 and remains 25 basis points above baseline in 2025. - Core inflation increases by about 20–30 basis points in 2024–25. - Monetary policy tightens; rates in advanced economies and emerging markets about 30 to 40 basis points higher in 2025. - Global activity lower by as much as 0.4 percent by 2025. - Effect broadly similar across advanced and emerging markets; within advanced economies effect slightly larger in Europe than the United States due to greater shipping cost impact. - Global divergence scenario - Dollar appreciates in nominal terms by 2 percent against advanced economy currencies and by 5 percent against emerging market economies in 2024. - Initial support to emerging market export demand from depreciation partially offsets tighter domestic financial conditions. - Global negative implications build in 2025 as tighter financial conditions reduce activity outside the United States. - Global output falls by 0.4 percent in 2025. - Global headline inflation falls by about 25 basis points below baseline in 2025. ### Commodity market developments (Special Feature highlights) - Primary commodity prices declined slightly between August 2023 and February 2024, driven by a decrease in oil prices. - Oil market - After breaking $95 a barrel in late September, oil prices decreased by 4.2 percent between August 2023 and February 2024, when they stood at a monthly average of $80.70. - Futures markets suggest oil prices will average $78.60 per barrel in 2024 (slide by 2.5 percent year over year) and fall to $67.50 in 2029. - Upside risks: escalation of Middle East conflict and attacks on Russian oil infrastructure. - Downside risks: slowdown in Chinese oil demand and strong non-OPEC supply growth, possibly coupled with a rise in OPEC+ supply. - Red Sea tensions led to a 50 percent rise in global freight rates of oil product tankers; prices on Middle East to Europe route increased by 200 percent from mid-November 2023 to mid-March 2024. - Russian oil exports to China and India were mostly above the Group of Seven price cap since the second half of 2023, at a $15–$20 discount (based on Argus data). - Natural gas - TTF prices in Europe fell 24.4 percent from August 2023 to $8.10 a million British thermal units (MMBtu) in February 2024. - Asian LNG prices declined by 24.9 percent. - US Henry Hub prices decreased by 32.3 percent. - Futures: TTF prices average $9.45 in 2024, decreasing to $8.73 in 2029. - Henry Hub prices may rise from an average of $2.66 per MMBtu in 2024 to $3.63 in 2029. - US export capacity expected to almost double from 11.4 billion cubic feet a day (bcf/d) to 21.1 bcf/d until 2027 (US Energy Information Administration). - Metals and gold - IMF base metals price index rose by 4.7 percent from August 2023 to February 2024. - Iron ore prices increased by 14.9 percent due to record steel production in China. - Uranium prices rose by 75.3 percent to their highest level since 2007. - Gold prices rose by 5.5 percent (supported by safe haven demand and geopolitical tensions). - Agricultural commodities - IMF food and beverages price index gained 6.0 percent between August 2023 and February 2024. - Cereals prices declined by 7.2 percent; vegetable oils declined by 10.9 percent. - Cocoa prices increased by 64.2 percent; coffee prices increased by 18.2 percent. - Rubber prices jumped 39.8 percent due to output decline following a novel leaf disease in Asia. - Coffee price pressures influenced by Red Sea tensions leading some consumers to switch from Asian to Brazilian imports. _Italic: Source — IMF staff calculations and World Economic Outlook, April 2024._ ### 25.9 percent as demand outstripped supply growth, ### 25.9 percent as demand outstripped supply growth, ### Commodity price volatility and shocks - The pandemic, the war in Ukraine, and the conflict in Gaza and Israel generated shocks that led to a surge in commodity price volatility. - Volatility destabilized inflation and made fiscal and monetary policy more difficult, especially for low-income and commodity-exporting countries. - Risks to the price outlook are balanced: - Upside risks: further trade disruptions in the Black Sea and new food export restrictions. - Downside risk: larger-than-expected harvests constitute the most important downside risk. ### The Power of Prices: scope and questions - Key questions addressed: - To what extent are commodity supply and demand slow to react? - Is demand more price sensitive than supply? - Do elasticities differ across energy, agricultural, and mineral commodities? - What policies make commodity supply and demand more reactive? ### Methodology and data - Presents a consistently identified and estimated set of price elasticities of demand and supply for a broad range of commodities. - Uses a granular instrumental variable approach (Gabaix and Koijen, forthcoming) combined with an annual cross-country data set on agricultural goods, energy, and metals from 1960 to 2021. - Data sources include World Bank (2024), IEA (2024), FAO (2023), Bems and others (2023), Schwerhoff and Stuermer (2020), among others. - Online Annex 1.1 provides data descriptions and the methodology. ### Commodity market concentration and role of shocks - Methodology exploits idiosyncratic changes in commodity production and consumption in individual countries to estimate average global price elasticities; this requires markets to be highly concentrated. - Example: For palm oil the production HHI is 0.4, roughly 80 times higher than the HHI if all 195 countries had the same market share. - Country-specific idiosyncratic shocks are a substantial driver of fluctuations in global commodity production and consumption, though common factors are, on average, the stronger driver. - Common factors have increased especially in industrial commodity output and in consumption of both food and industrial commodities in the past decade. - For food commodities, idiosyncratic shocks in production are bigger than those in consumption; this is not the case for industrial commodities. - Agricultural production is more susceptible to idiosyncratic country-specific shocks such as droughts, flooding, or pests. ### Elasticities: key findings (supply and demand) - Overall conclusion: commodity demand and supply are generally price inelastic, with notable differences across commodity types. - Supply elasticities: - Metals, especially copper and zinc, tend to have the lowest supply elasticities; copper and zinc have a supply elasticity close to zero. - Cereals show a supply elasticity of about 0.6 (implying that a 10 percent increase in prices raises output by 6 percent within a year). - Perennial crops (coffee, palm oil, cocoa) have smaller short-term supply elasticities than annual crops; typical time to fruit: palm oil ~ two years, cocoa ~ five years. - Energy commodity supply elasticities tend to be between mineral and agricultural commodity elasticities. - Demand elasticities: - Agricultural goods: rice shows a price elasticity of demand close to zero, probably reflecting that only about 10 percent of output is internationally traded and that rice prices are typically subsidized in Asia. - Elasticities for tea, cotton, and wheat are above 0.4. - Crude oil and coal show demand elasticities below 0.2. - Copper and zinc have demand elasticities close to zero. - Lead and tin have demand elasticities between 0.2 and 0.3. - Commodities-specific notes: - Within cereals, cross-elasticities of demand allow for substitution, which contributed to wheat prices coming down below prewar levels after spiking at the start of the war in Ukraine. - Mineral commodities are particularly inelastic on both supply and demand; energy commodities are intermediate. ### Time dynamics: responsiveness over horizons - Supply and demand become more responsive over time as markets adjust to shocks. - Long-term multipliers show notable differences across commodities and horizons: - Most agricultural commodities: supply responses are flat over a five-year horizon. - Perennial crops (coffee, cocoa, rubber): statistically significant strong peak about two to three years after a shock. - Most metals and energy: supply elasticities are upward sloping over time; only copper’s upward slope is statistically significant. - Demand side estimates are generally not very precisely estimated; metals show the largest increases in multipliers over longer horizons. - For most agricultural commodities, demand multipliers do not become larger over time. - Agricultural goods tend to be more responsive to shocks than minerals and energy, consistent with smaller price volatility for agricultural goods versus metals and energy. - Agricultural commodities see the least increase in responsiveness after a couple of years, whereas mineral commodities become more responsive. ### Conclusions and policy implications - Main empirical takeaway: commodity demand and supply are generally price inelastic, with differences across commodity groups (perennial vs annual crops; metals vs energy vs agriculture). - Policy recommendations: - Countries exposed to commodity markets with relatively low elasticities, especially metals, should build fiscal buffers and monetary policy space to prepare for larger impacts of possible shocks. - Replacing energy and agricultural subsidies with targeted transfers would help increase the demand and supply elasticities of many commodities and could reduce their price volatility. - International trade can play a prominent role in smoothing out commodity shocks and buffering against their economic impact; this will be particularly relevant amid increasing geopolitical tensions and trade fragmentation and for critical minerals for the energy transition. *Source: IMF staff analysis presented in the Special Feature "The Power of Prices: How Fast Do Commodity Markets Adjust to Shocks?" from the World Economic Outlook—April 2024.* ### Annex Table 1.1.4. Middle East and Central Asia Economies: Real GDP, Consumer Prices, Current Account Balance, and ### Annex Table 1.1.4. Middle East and Central Asia Economies: Real GDP, Consumer Prices, Current Account Balance, and Unemployment ### Regional aggregate — Middle East and Central Asia (summary) - Real GDP (Projections): 2023: 2.0, 2024: 2.8, 2025: 4.2 - Consumer Prices (Projections): 2023: 16.7, 2024: 15.5, 2025: 11.8 - Current Account Balance (Percent of GDP, Projections): 2023: 4.0, 2024: 1.8, 2025: 1.4 - Unemployment (Percent, Projections): 2023: . . .. . .. . . ### Oil Exporters (aggregate) - Real GDP (Projections): 2023: 2.1, 2024: 2.8, 2025: 4.4 - Consumer Prices (Projections): 2023: 11.4, 2024: 10.3, 2025: 9.1 - Current Account Balance (Projections): 2023: 6.4, 2024: 4.0, 2025: 3.1 - Unemployment (Projections): 2023: . . .. . .. . . Selected oil-exporting economies (2023, 2024, 2025 — Real GDP; 2023, 2024, 2025 — Consumer Prices; 2023, 2024, 2025 — Current Account Balance; 2023, 2024, 2025 — Unemployment) - Saudi Arabia - Real GDP: 2023: –0.8, 2024: 2.6, 2025: 6.0 - Consumer Prices: 2023: 2.3, 2024: 2.3, 2025: 2.0 - Current Account Balance: 2023: 3.9, 2024: 0.5, 2025: –0.6 - Unemployment: . . .. . .. . . - Iran - Real GDP: 2023: 4.7, 2024: 3.3, 2025: 3.1 - Consumer Prices: 2023: 41.5, 2024: 37.5, 2025: 32.5 - Current Account Balance: 2023: 4.4, 2024: 3.6, 2025: 3.4 - Unemployment: 2023: 9.0, 2024: 8.9, 2025: 8.8 - United Arab Emirates - Real GDP: 2023: 3.4, 2024: 3.5, 2025: 4.2 - Consumer Prices: 2023: 1.6, 2024: 2.1, 2025: 2.0 - Current Account Balance: 2023: 9.3, 2024: 7.8, 2025: 6.9 - Unemployment: . . .. . .. . . - Kazakhstan - Real GDP: 2023: 5.1, 2024: 3.1, 2025: 5.6 - Consumer Prices: 2023: 14.6, 2024: 8.7, 2025: 7.0 - Current Account Balance: 2023: –3.8, 2024: –4.5, 2025: –2.7 - Unemployment: 2023: 4.8, 2024: 4.8, 2025: 4.8 - Algeria - Real GDP: 2023: 4.2, 2024: 3.8, 2025: 3.1 - Consumer Prices: 2023: 9.3, 2024: 7.6, 2025: 6.4 - Current Account Balance: 2023: 2.2, 2024: 0.1, 2025: –1.5 - Unemployment: . . .. . .. . . - Iraq - Real GDP: 2023: –2.2, 2024: 1.4, 2025: 5.3 - Consumer Prices: 2023: 4.4, 2024: 4.0, 2025: 4.0 - Current Account Balance: 2023: 2.6, 2024: –3.6, 2025: –5.1 - Unemployment: . . .. . .. . . - Qatar - Real GDP: 2023: 1.6, 2024: 2.0, 2025: 2.0 - Consumer Prices: 2023: 3.1, 2024: 2.6, 2025: 2.4 - Current Account Balance: 2023: 18.7, 2024: 15.6, 2025: 13.2 - Unemployment: . . .. . .. . . - Kuwait - Real GDP: 2023: –2.2, 2024: –1.4, 2025: 3.8 - Consumer Prices: 2023: 3.6, 2024: 3.2, 2025: 2.7 - Current Account Balance: 2023: 32.8, 2024: 30.1, 2025: 27.1 - Unemployment: . . .. . .. . . - Oman - Real GDP: 2023: 1.3, 2024: 1.2, 2025: 3.1 - Consumer Prices: 2023: 0.9, 2024: 1.3, 2025: 1.5 - Current Account Balance: 2023: 1.8, 2024: 2.7, 2025: 2.1 - Unemployment: . . .. . .. . . - Azerbaijan - Real GDP: 2023: 1.1, 2024: 2.8, 2025: 2.3 - Consumer Prices: 2023: 8.2, 2024: 3.5, 2025: 5.0 - Current Account Balance: 2023: 9.9, 2024: 8.5, 2025: 8.1 - Unemployment: 2023: 5.6, 2024: 5.5, 2025: 5.5 - Turkmenistan - Real GDP: 2023: 2.0, 2024: 2.3, 2025: 2.3 - Consumer Prices: 2023: –1.7, 2024: 5.0, 2025: 7.9 - Current Account Balance: 2023: 4.8, 2024: 4.1, 2025: 2.8 - Unemployment: . . .. . .. . . - Bahrain - Real GDP: 2023: 2.6, 2024: 3.6, 2025: 3.2 - Consumer Prices: 2023: 0.1, 2024: 1.4, 2025: 1.8 - Current Account Balance: 2023: 6.3, 2024: 6.9, 2025: 5.3 - Unemployment: . . .. . .. . . ### Oil Importers (aggregate) - Real GDP (Projections): 2023: 1.8, 2024: 2.7, 2025: 4.0 - Consumer Prices (Projections): 2023: 25.7, 2024: 24.5, 2025: 16.3 - Current Account Balance (Projections): 2023: –2.9, 2024: –4.6, 2025: –3.5 - Unemployment (Projections): . . .. . .. . . Selected oil-importing economies (2023, 2024, 2025 — Real GDP; 2023–2025 — Consumer Prices; 2023–2025 — Current Account Balance; 2023–2025 — Unemployment) - Egypt - Real GDP: 2023: 3.8, 2024: 3.0, 2025: 4.4 - Consumer Prices: 2023: 24.4, 2024: 32.5, 2025: 25.7 - Current Account Balance: 2023: –1.2, 2024: –6.3, 2025: –2.4 - Unemployment: 2023: 7.2, 2024: 7.1, 2025: 7.0 - Pakistan - Real GDP: 2023: –0.2, 2024: 2.0, 2025: 3.5 - Consumer Prices: 2023: 29.2, 2024: 24.8, 2025: 12.7 - Current Account Balance: 2023: –0.7, 2024: –1.1, 2025: –1.2 - Unemployment: 2023: 8.5, 2024: 8.0, 2025: 7.5 - Morocco - Real GDP: 2023: 3.0, 2024: 3.1, 2025: 3.3 - Consumer Prices: 2023: 6.1, 2024: 2.2, 2025: 2.5 - Current Account Balance: 2023: –1.5, 2024: –2.6, 2025: –2.9 - Unemployment: 2023: 13.0, 2024: 12.0, 2025: 11.5 - Uzbekistan - Real GDP: 2023: 6.0, 2024: 5.2, 2025: 5.4 - Consumer Prices: 2023: 10.0, 2024: 11.6, 2025: 9.7 - Current Account Balance: 2023: –4.9, 2024: –4.9, 2025: –4.5 - Unemployment: 2023: 8.4, 2024: 7.9, 2025: 7.4 - Sudan - Real GDP: 2023: –18.3, 2024: –4.2, 2025: 5.4 - Consumer Prices: 2023: 171.5, 2024: 145.5, 2025: 62.7 - Current Account Balance: 2023: –5.4, 2024: –6.9, 2025: –11.0 - Unemployment: 2023: 46.0, 2024: 49.5, 2025: 48.2 - Tunisia - Real GDP: 2023: 0.4, 2024: 1.9, 2025: 1.8 - Consumer Prices: 2023: 9.3, 2024: 7.4, 2025: 6.9 - Current Account Balance: 2023: –2.5, 2024: –3.5, 2025: –3.7 - Unemployment: 2023: 16.4, 2024: . . .. . .. . . - Jordan - Real GDP: 2023: 2.6, 2024: 2.6, 2025: 3.0 - Consumer Prices: 2023: 2.2, 2024: 2.7, 2025: 2.4 - Current Account Balance: 2023: –7.0, 2024: –6.3, 2025: –4.5 - Unemployment: . . .. . .. . . - Georgia - Real GDP: 2023: 7.5, 2024: 5.7, 2025: 5.2 - Consumer Prices: 2023: 2.5, 2024: 2.6, 2025: 4.2 - Current Account Balance: 2023: –4.3, 2024: –5.8, 2025: –5.6 - Unemployment: 2023: 16.4, 2024: 15.7, 2025: 16.0 - Armenia - Real GDP: 2023: 8.7, 2024: 6.0, 2025: 5.2 - Consumer Prices: 2023: 2.0, 2024: 2.0, 2025: 3.1 - Current Account Balance: 2023: –1.9, 2024: –2.8, 2025: –3.6 - Unemployment: 2023: 12.5, 2024: 13.0, 2025: 13.5 - Tajikistan - Real GDP: 2023: 8.3, 2024: 6.5, 2025: 4.5 - Consumer Prices: 2023: 3.7, 2024: 4.9, 2025: 6.3 - Current Account Balance: 2023: –0.7, 2024: –2.1, 2025: –2.2 - Unemployment: . . .. . .. . . - Kyrgyz Republic - Real GDP: 2023: 4.2, 2024: 4.4, 2025: 4.2 - Consumer Prices: 2023: 10.8, 2024: 6.7, 2025: 6.6 - Current Account Balance: 2023: –30.4, 2024: –9.5, 2025: –8.0 - Unemployment: 2023: 9.0, 2024: 9.0, 2025: 9.0 - West Bank and Gaza - Real GDP: 2023: –6.1, 2024: . . .. . .. . . - Consumer Prices: 2023: 5.9, 2024: . . .. . .. . . - Current Account Balance: 2023: –13.1, 2024: . . .. . .. . . - Unemployment: 2023: 28.7, 2024: . . .. . .. . . - Mauritania - Real GDP: 2023: 4.8, 2024: 5.1, 2025: 5.5 - Consumer Prices: 2023: 4.9, 2024: 2.8, 2025: 4.0 - Current Account Balance: 2023: –11.2, 2024: –11.7, 2025: –9.2 - Unemployment: . . .. . .. . . ### Memorandum and regional groupings - Caucasus and Central Asia - Real GDP (Projections): 2023: 4.9, 2024: 3.9, 2025: 4.8 - Consumer Prices: 2023: 9.7, 2024: 7.7, 2025: 7.1 - Current Account Balance: 2023: –1.5, 2024: –1.9, 2025: –1.3 - Unemployment: . . .. . .. . . - Middle East, North Africa, Afghanistan, and Pakistan - Real GDP (Projections): 2023: 1.6, 2024: 2.6, 2025: 4.1 - Consumer Prices: 2023: 17.7, 2024: 16.6, 2025: 12.4 - Current Account Balance: 2023: 4.8, 2024: 2.4, 2025: 1.8 - Unemployment: . . .. . .. . . - Middle East and North Africa - Real GDP (Projections): 2023: 1.9, 2024: 2.7, 2025: 4.2 - Consumer Prices: 2023: 16.0, 2024: 15.4, 2025: 12.4 - Current Account Balance: 2023: 5.3, 2024: 2.7, 2025: 2.1 - Unemployment: . . .. . .. . . - Israel - Real GDP: 2023: 2.0, 2024: 1.6, 2025: 5.4 - Consumer Prices: 2023: 4.2, 2024: 2.4, 2025: 2.5 - Current Account Balance: 2023: 4.7, 2024: 5.6, 2025: 4.2 - Unemployment: 2023: 3.5, 2024: 3.7, 2025: 3.8 *Source: IMF staff estimates.* ### Introduction ### Introduction ### Context: recent tightening and supply shocks - Since late 2021, in a bid to restore price stability, central banks around the world have raised policy interest rates at a speed, degree, and breadth unprecedented in at least 40 years. - Reopening-related supply-chain disruptions and the war in Ukraine hit post-lockdown economies with a series of supply shocks. These shocks, combined with extraordinarily supportive fiscal and monetary policies during the pandemic, supercharged inflation to levels not seen in decades. - Given the sudden rise in interest rates, many observers predicted a sharp fall in growth for 2023. In the end, global growth proved surprisingly resilient despite higher policy rates; economic activity outpaced expectations in most countries, and employment remained robust even as inflation retreated significantly. - Asset prices, including house prices, respond faster than aggregate macro variables; peak macro responses to monetary policy are often estimated to be about two years. Economists have found some support for asymmetric effects: rising policy rates have larger effects than similar-sized declines. ### Research focus and questions - This chapter investigates the transmission of monetary policy across countries and over time through the lens of mortgage and housing markets. - Rationale: - Mortgages are the largest liability of households; housing is often households’ only significant form of wealth. - Real estate accounts for a large share of consumption, investment, employment, and consumer prices in most economies. - House prices, as a macrocritical asset price, can offer early clues as to where households are feeling the pinch of monetary policy. - Mortgage and housing markets vary significantly across countries, facilitating assessment of variability in transmission. - Four main questions: - Where are real estate and mortgage markets now? How have they evolved following the global financial crisis, the pandemic, and the recent monetary tightening? - Conceptually, what are the housing channels of monetary policy transmission? How are housing channels tied to mortgage and housing market characteristics? - How do the housing channels vary across countries? - Have the housing channels weakened in recent years? ### Data, methods, and modeling - New data leveraged: - Monetary policy surprises against analyst predictions, to identify exogenous changes in interest rates. - The prevalence of fixed-rate mortgages across countries, from public sources and national authorities. - A new regional data set of house prices and real activity. - Empirical methods follow Jordà (2005), Stock and Watson (2018), and Chen and others (2023). - Model simulations assess joint effects of the prevalence of fixed-rate mortgages and regulatory loan-to-value (LTV) limits. - The chapter builds on earlier IMF work and a long academic literature. ### Main findings - Mortgage and real estate markets have undergone several shifts: - At the beginning of the recent hiking cycle and after a long period of low interest rates, mortgage interest payments were historically low, and the average maturity and share of mortgages subject to fixed rates were high in many countries. - Low rates and structural pandemic-related changes led to rapid growth in house prices; residential real estate prices remain well above prepandemic levels but have stabilized or declined in some economies in 2023. Country experiences vary widely. - Housing channels vary significantly across countries; mortgage market characteristics matter: - Transmission of monetary policy is stronger in countries where: - fixed-rate mortgages (FRMs) are less common; - home buyers are more leveraged on account of less-restrictive regulatory LTV limits; - household debt is high. - Model simulations suggest these effects reinforce each other. Restrictive regulatory LTV limits and household debt may dampen transmission more in the short term, delaying transmission. - Housing market characteristics also matter: - Transmission is stronger where (1) housing supply is more restricted and (2) house prices have recently been overvalued. - Evidence suggests these two housing market characteristics strengthen transmission more when monetary policy is tightening than when it is loosening. - A high prevalence of FRMs dampens transmission more in a tightening cycle. - The housing channels have weakened in several countries recently: - Since the global financial crisis and during the pandemic, the prevalence of FRMs has increased, regulatory LTV limits have been tightened, and population has shifted to less-supply-constrained areas—factors that weaken transmission. - These dampening developments are counterbalanced in some cases by increases in house prices in already-overvalued areas and in household debt, which would strengthen the effects of monetary policy. ### Stylized facts and background on real estate markets - Postglobal financial crisis and through the 2010s, policy rates were kept low and were brought close to zero in advanced economies amid weak growth and low inflation. In 2020, the pandemic prompted another round of policy rate cuts; major central banks expanded asset purchase programs and other central banks initiated new such programs, keeping long-term rates low. - Many households used low rates to secure low-cost mortgages. At the start of the recent hiking cycle, effective mortgage rates had reached their lowest point in decades in many countries. For example, effective mortgage rates in France, Germany, and the United States reached 1.5, 1.7, and 3.3 percent, respectively, in early 2022 after declining from 4.0, 4.5, and 4.5 percent in 2011, respectively. - Fixed-rate mortgages became more common and mortgages became long-dated in some countries, often driven by refinancing of old loans. - Drawing lessons from the global financial crisis, many authorities tightened macroprudential policies related to housing financing at the turn of the 2010s; average creditworthiness and leverage of households generally improved. - During the pandemic, low rates and structural changes led to rapid growth in house prices globally; house prices often grew faster than income, lowering affordability and boosting rents in many countries. - Pandemic-era labor-practice changes (such as remote work) created headwinds for commercial real estate; price drops—pronounced for offices in the United States—have persisted since economies reopened. Rising borrowing costs add strains as low-rate loans require refinancing over time. - Rising borrowing costs cooled building activity in most countries, depressing supply already insufficient following the global financial crisis, while high inflation—particularly in raw materials—triggered a surge in construction costs. ### Caveats and chapter structure - Caveats: - Empirical analyses are constrained by data availability across economies and over time; lack of data precludes study of rents within this chapter. - The chapter focuses narrowly on residential real estate and household mortgage characteristics, abstracting from whether banks or governments share interest rate risk and ignoring other transmission channels. - It is not technically feasible to gather all characteristics within the same framework; analyses may not capture general equilibrium effects. - Structure: - The chapter documents trends in mortgage and housing markets; offers a conceptual framework linking monetary policy effects to mortgage and housing market characteristics; provides cross-country evidence of heterogeneous effects; assesses changes in strength of housing channels over time; and draws lessons for monetary and macroprudential policymakers. *Source: Introduction, Chapter 2, “Feeling the Pinch? Tracing the Effects of Monetary Policy through Housing Markets,” World Economic Outlook, April 2024.* ### Annex Figure 2.2.5). Meanwhile, elevated rates on ### Annex Figure 2.2.5). Meanwhile, elevated rates on ### Key empirical patterns - Since the beginning of the current hiking cycle, nominal house prices have declined in about a third of countries in the sample considered here but continued to rise elsewhere. Regardless, house prices remained elevated at the end of 2023 in most countries. - Household consumption has evolved differently across countries; house prices and consumption have often moved in the same direction, rising in tandem in some countries (for example, Colombia and Hungary) and declining in others (for example, Germany and Sweden). - Reduced housing transactions were driven in part by elevated rates on new mortgages and by homeowners who had locked in low fixed rates and were reluctant to sell (see, for example, Fonseca and Liu 2023 for the United States). - House prices and residential investment together represent about 70 percent of GDP in most economies (Online Annex Figure 2.2.1). ### The housing channels of monetary policy transmission (conceptual) - The figure summarizes seven channels linking policy rates to household consumption and residential investment; the figure is stylized and abstracts from second-round effects from consumption and investment back to house prices and credit. - Channel 1 — Cash flow channel: rising policy rates directly depress consumption by homeowners with adjustable-rate mortgages who cannot borrow easily (Di Maggio and others 2017; Flodén and others 2021). This operates even in countries with high incidences of fixed-rate mortgages if refinancing is not costly, but only when rates are lowered. - Channel 2 — Expectations/risk premium channel: house prices are sensitive to changes in interest rates through evolving expectations about the future path of monetary policy and house prices; falling expected future prices reduce present demand and can trigger higher mortgage rates and further declines in demand. - Channel 3 — Wealth channel: falling house prices reduce homeowners’ consumption because home values are often their main form of wealth (Kaplan, Mitman, and Violante 2020). - Channel 4 — Collateral channel: reduced home values weaken collateral, reducing access to credit and thereby lowering household consumption (Kiyotaki and Moore 1997; Iacoviello and Neri 2010; Mian, Rao, and Sufi 2013; Bhutta and Keys 2016; Beraja and others 2019). - Channel 5 — Interest rate channel: higher policy rates transmit into higher mortgage rates, reducing demand for credit and housing (van Binsbergen and Grotteria 2023; Mian and Sufi 2009; Jordà, Schularick, and Taylor 2015). - Channel 6 — Bank lending channel: higher funding costs or lower deposits can reduce bank lending. - Channel 7 — Balance sheet channel: lenders reduce credit to riskier households as borrower net worth falls and default risk rises. - Interactions and amplifications: the cash flow channel (1) is linked to the interest rate channel (5); wealth and collateral channels (3 and 4) are stronger where household debt is higher or LTV limits are looser; the expectations/risk premium channel (2) is stronger where preexisting overvaluation and supply restrictions are greater. ### Cross-country heterogeneity and mortgage market characteristics (empirical) - Empirical approach: local projections instrumental variable framework applied to country-level panels, using monetary policy shocks based on deviations of actual rate decisions from analysts’ expectations. - Sample coverage and data notes: - Panel of 33 emerging market and advanced economies. - Controls include time and country fixed effects and eight lags of changes in the dependent variable and other macroeconomic outcomes. - Sample period shown in figures covers 1998:Q4 to 2023:Q1. - Three mortgage market characteristics studied: 1. Share of FRMs (fixed-rate mortgages) in the stock of outstanding mortgages (FRMs defined as nominal payments that do not reset within a year). 2. Regulatory loan-to-value (LTV) limits on mortgages. 3. Ratio of household debt to GDP. - Cross-country heterogeneity examples: - Fixed-rate mortgages are rare or nonexistent in some countries (for example, Finland and South Africa) and constitute the majority in others (Belgium, Mexico, and the United States). - Regulatory LTV limits can be as restrictive as 45 percent in Korea, whereas in many countries LTV limits are as high as 100 percent or more (France, Germany, and the United States). - Household debt is below 50 percent of GDP in some (for example, Chile, Colombia, and Israel) and exceeds 100 percent of GDP in others (Australia, Canada, and Norway). ### Key empirical findings on differential transmission - Fixed-rate mortgages (FRMs) and consumption: - High share of FRMs significantly dampens the transmission of monetary policy to consumption relative to when FRMs are rare, with these differences becoming significant after five quarters. - There are no significant differences in the transmission of monetary policy to house prices between high-FRM and low-FRM countries. - LTV limits and household debt: - The analysis examines differential effects on both house prices and consumption depending on whether LTV limits are below 100 percent ("LTV restricted") or not, and whether household debt to GDP is above or below the sample median ("High household debt"/"Low household debt"). - Magnitude reference: plotted cumulative percentage point responses are to a 100 basis point change in policy rates; figures show horizons in quarters (0–8) with 90 percent confidence intervals. - Statistical notation in figures: - Two groups per characteristic: “High FRM” if share of FRMs is above the sample median, “Low FRM” otherwise; “LTV restricted” if LTV limits are below 100 percent, “LTV not restricted” otherwise; “High household debt” if household debt to GDP is above the sample median, “Low household debt” otherwise. - Diamonds indicate where differences between coefficients are statistically significant at least at the 10 percent level. ### Implications and channels mapping - The cash flow channel (1) is stronger where households are directly exposed to changes in mortgage rates (active interest rate channel 5): e.g., where fixed-rate mortgages are rare, household debt is higher, or macroprudential constraints (loan-to-value limits) are looser. - The expectations/risk premium channel (2) is amplified where preexisting overvaluation is greater and housing supply is more restricted. - The wealth and collateral channels (3 and 4) are more pronounced where household debt is higher or LTV limits are looser, and in regions with higher housing supply restrictions where prices respond more strongly to monetary policy. - The interest rate channel (5) will have more muted effects if regulatory LTV limits are stricter because borrowing shifts toward wealthier households who rely less on debt. *Source: IMF staff.* ### CHAPTER 2 FEELINg THE PINCH? TRaCINg THE EFFECTS OF MONETaRy POLICy THROUgH HOUSINg MaRKETS ### CHAPTER 2 FEELINg THE PINCH? TRaCINg THE EFFECTS OF MONETaRy POLICy THROUgH HOUSINg MaRKETS ### Fixed-Rate Mortgages (FRMs) and the Timing of the Cash-Flow Channel - Many consumers do not feel the pinch of rising policy rates until the rate on their mortgage resets, temporarily reducing the strength of the cash flow channel. - The differential effect of FRMs on transmission is more relevant when monetary policy is tightening than when it is loosening. - When policy rates are lowered, borrowers with FRMs who can refinance may reduce monthly mortgage payments, so FRMs limit transmission less in easing episodes. - When policy rates are rising, most borrowers with FRMs have no incentive to refinance and prefer to keep lower fixed payments, delaying transmission (see Figure 2.8). ### Regulatory Loan-to-Value (LTV) Limits and Transmission Speed - When regulatory LTV limits are above 100 percent (that is, when they are not restricted), house prices and private consumption respond more forcefully to monetary policy. - Example: Eight quarters after a 100 basis point increase (decline) in policy rates: - House prices drop (rise) by 1 percentage point when LTV limits are restricted and by 4 percentage points when LTV limits are not restricted. - The consumption effect materializes significantly faster when LTV limits are not restricted, though differences dissipate after four quarters; by the fourth quarter the effect when LTVs are restricted is about half of what it is when they are not. - Tighter LTV limits typically restrict poorer households’ borrowing more acutely, reducing the borrower pool to relatively less marginal-propensity-to-consume households. - Cash-out refinancing is rare in most countries, so collateral and wealth channels are likely less relevant than the interest rate channel at the time of home purchases. ### Household Indebtedness Strengthens and Accelerates Transmission - Where households are more indebted, monetary policy has a stronger effect on house prices. - Example: Eight quarters after a change in monetary policy, nominal house prices respond about 3 percentage points more when household debt ratios are above the sample median relative to when they are below. - The consumption response is significantly faster if debt is higher, although statistically the difference winds down after three quarters. - Higher household debt implies greater dependence on mortgages for property purchases, making housing transactions more affected by policy-rate changes through credit demand and the interest rate channel. - Ultimately, exposure of existing mortgage borrowers to interest rate changes matters most, taking precedence over collateral and wealth channels. ### Complementarity of LTV Limits and Prevalence of FRMs (Model Simulations) - Two-agent New Keynesian model simulations (Chen and others 2023) indicate that prevalence of FRMs and the effects of LTV limits reinforce each other. - Quantified model comparisons (response to a 100 basis point change in policy rates): - Moving from high to low FRMs given loose LTV limits: transmission rises by 17 percent (red to yellow line). - Moving from high to low FRMs given tight LTV limits: transmission rises by 13 percent (blue to green line). - Moving from loose to tight LTV limits given low FRMs: transmission rises by 23 percent (green to yellow line). - Moving from loose to tight LTV limits given high FRMs: transmission rises by 19 percent (blue to red line). - The weakest transmission to household consumption occurs under more restrictive LTV limits and highly prevalent FRMs. ### Local Housing Market Characteristics: Supply Restrictions and Overvaluation - Housing supply restrictions (proxied by population density) and house price overvaluation (deviations from regional long-term house-price-to-income ratio) exhibit right-tailed distributions, suggesting nonlinearities matter. - Supply restrictions: - Following a 100 basis point tightening (loosening), nominal house prices decline (rise) by an additional 3 percentage points after eight quarters in areas with restricted housing supply compared with less restricted areas. - Real GDP per capita undergoes an additional decline (rise) of 2 percentage points at peak in supply-restricted regions. - The house-price effect is about 50 percent larger than the average effect of monetary policy on house prices; the GDP per capita effect is about one-third larger than the corresponding average. - Effects in supply-restricted regions tend to be more back-loaded. - House price overvaluation: - Following a 100 basis point tightening (loosening), the peak fall (rise) in nominal house prices is 1.5 percentage points greater in areas with recent overvaluation relative to those without. - Real GDP per capita declines (rises) an extra 1 percentage point in regions with recent overvaluation (about two-thirds of the average effect). - The differential effect on GDP per capita is back-loaded; house prices peak at about five quarters. - Mechanisms: expectations, collateral, and wealth channels amplify downturns where overoptimism and excessive leverage preceded the tightening. ### Asymmetry: Effects Larger When Policy Tightens - Supply constraints and overvalued house prices matter more when rates are rising; symmetry can be statistically rejected for house prices in the first two quarters. - A potential explanation is the leverage-distribution shape: fewer households become borrowing unconstrained after easing than those who become more constrained when policy tightens. ### Cross-Country Variation and Recent Evolution - Cross-country heat map (based on 2022 data or latest available) shows large variation in monetary policy transmission via housing channels across countries, focusing on: - Share of fixed-rate mortgages - Regulatory LTV limits - Household debt - Housing supply restrictions - Degree of house price overvaluations - Examples from the heat map: - Australia and Japan show stronger housing-channel transmission with low shares of FRMs, less-restrictive LTV limits, high household debt (Japan only to some extent), and elevated population in supply-restricted areas. - Colombia, Hungary, and Israel are more likely to exhibit weaker transmission, with notably low household debt and supply constraints. - Caveats: heat map columns are not comparable or aggregable; the figure focuses solely on housing channels while other channels (for example, the exchange rate channel) may be important in some economies. - The ranking broadly lines up with actual changes in house prices and real consumption since the start of each country’s most recent hiking cycle, though many other shocks matter. ### Evidence of Weakened Housing Channels over Time - Mortgage and housing market characteristics change slowly over time and across countries. - Fixed-rate mortgages have become more prevalent in many countries since the global financial crisis, with the increase driven by low rates. - Regulatory LTV limits have either tightened or remained stable (continuation indicated; further details in subsequent text). *Source: CHAPTER 2 FEELINg THE PINCH? TRaCINg THE EFFECTS OF MONETaRy POLICy THROUgH HOUSINg MaRKETS, International Monetary Fund | April 2024* ### Annex Figure 2.2.6). Household debt ratios have ### Annex Figure 2.2.6). Household debt ratios have ### Changes in household debt and housing markets - Household debt ratios have increased in some countries, notably Chile, France, and Korea, but decreased in others, such as Denmark, Ireland, and Spain (Online Annex Figure 2.2.7). - Housing markets underwent notable changes during the pandemic (Online Annex Figure 2.2.8). - National-level housing supply is now likely to be more elastic in most countries analyzed as a result of migration from densely populated urban areas to less dense rural or suburban areas during the pandemic years. - House price overvaluation changes have been more balanced: - In some countries, areas that were overvalued in 2019 have seen stagnant or declining price-to-income ratios (for example, Finland and Hungary), as people moved away from previously overvalued regions. - In other countries, house price overvaluation has risen where house prices were already overvalued (for example, Mexico and The Netherlands). ### Measurement and data notes on housing and mortgage indicators - Fixed-rate mortgages are the share of the total outstanding stock, 2022:Q4 (or latest available). Fixed-rate mortgages exclude mortgages that adjust to inflation (as in Chile). - LTV limits are the regulatory loan-to-value limits, averaged across all mortgage types, 2021:Q4. - HH debt is the household credit-to-GDP ratio, 2022:Q4. - Supply constraints are the proportion of population living in areas with high population density, 2022:Q4 (or latest available). Regions above the 90th percentile of population density within each country are defined as high-population-density areas. - Overvaluation is the median price-to-income ratio (PIR) in overvalued areas, 2022:Q4 (or latest available). A region is defined as overvalued if its PIR is above the 75th percentile of its regional time series. - For each of the five criteria, countries obtain a score between 1 and 4 reflecting their percentile in the cross-country distribution (Figure 2.12). Judgment is used for borderline cases. - In change analyses: fixed-rate mortgages change is measured from 2011:Q1 (or earliest available) to 2022:Q4 (or latest available); LTV limits change is from 2011:Q1 to 2021:Q4; HH debt change is from 2011:Q1 to 2022:Q4; supply constraints change is population growth differential between areas with high and low population density, from 2019:Q4 to 2022:Q4 (or latest available); overvaluation change is median PIR growth differential between overvalued and nonovervalued areas, from 2019:Q4 to 2022:Q4 (or latest available). - For change scoring, countries obtain a score between 1 and 3 reflecting their percentile in the cross-country distribution within positive and negative changes. Judgment is used for borderline cases. Gray cells indicate no change. White cells indicate missing data. ### Heterogeneity in monetary policy transmission - The heat map (Figure 2.14) summarizes how shifts in housing and mortgage characteristics imply changes in monetary policy transmission: - Shades of blue indicate changes that imply weakening in monetary policy transmission; shades of red indicate strengthening; gray represents no change. - Countries are ranked based on the order in Figure 2.12, with the strongest transmission at the top and the weakest at the bottom. - Country-level examples: - Canada, Chile, and Japan: changes suggest a strengthening of transmission, driven mainly by a declining or stable share of FRMs, an increase in debt, and more constrained housing supply. - Hungary, Ireland, Portugal, and the United States: characteristics have moved in the opposite direction, suggesting weakened transmission. - Global takeaway: the heat map points to a decline in the transmission of monetary policy through the cash flow, wealth, and collateral channels, albeit to varying degrees across countries. Contributing factors include increased adoption of fixed-rate mortgages, tighter LTV limits, lower debt, outmigration from densely populated areas, and house price deflation in some previously overvalued areas. - Caveat: the heat map ignores changes in channels of transmission beyond housing and thus gives only a partial view of the changing strength of monetary policy transmission. Rapid policy-rate increases over the last two years may also have affected transmission. ### Policy implications and recommended prudential measures - Broad conclusions: - Monetary policy affects economic activity through housing; the strength of these housing channels varies significantly across countries and has weakened recently in several economies. - A large body of literature establishes that tighter macroprudential regulation improves financial and economic stability; this chapter takes the level of regulation as given and finds that monetary policy may have smaller effects in countries with relatively tight regulation because borrowers are on average less leveraged. - For macroprudential authorities: - Tighter borrower-based macroprudential measures help financial and economic stability and allow monetary policy to focus on aggregate demand and price pressures. - For monetary authorities: - Deep, country-specific understanding of housing channels is important to calibrate and adjust policy. - In countries where housing channels are strong, monitoring housing market developments and changes in household debt service can help identify early signs of overtightening. - Where monetary policy transmission is weak, more forceful early action can be taken when signs of overheating and inflationary pressures first emerge. - Risks and cautions: - Fixed-rate mortgages have become more common in many countries, but fixation periods are often short; as rates on these mortgages reset over time, monetary policy transmission could suddenly become more effective and depress consumption. - Financial instability could follow if defaults rise abruptly—especially in countries where households are highly indebted or where bankruptcy laws favor borrowers. - Sharp pandemic-era house price rises have left some markets overvalued; these may be more likely to correct if rates remain high for long, particularly where macroprudential policies did not prevent leverage buildup. - Prudential recommendation for the next tightening cycle: - Prudential authorities should add instruments such as caps on debt-service-to-income ratios, if not already in place, to prevent financial stability side effects of monetary policy. - Summary judgement: the longer rates are kept high, the greater the likelihood that households will feel the pinch, even where so far they have been relatively sheltered. ### Interest rate pass-through in Europe (Box 2.1) - Pass-through heterogeneity: - In the postpandemic tightening cycle in Europe, pass-through seems highest to time deposits, followed by mortgages and to loans to nonfinancial corporations. - Relative to past cycles, pass-through in Europe has weakened somewhat, except for that to nonfinancial corporation time deposits and loans. - Effects on real activity depend on mortgage market characteristics such as prevalence of variable-rate mortgages and share of households with mortgages. - High pass-through to outstanding mortgages combined with a high stock of mortgages can imply large changes in household debt-service costs. - The annual increase in mortgage-servicing costs relative to mid-2022 varies across the euro area, from Portugal at 1.2 percent of GDP to Malta at virtually zero. - Note on methodology: pass-through is based on regression analysis in the spirit of Burstein and Gopinath (2014). The differences between solid bars are statistically significant at the 10 percent level or better. ### China: monetary policy transmission through the housing market (Box 2.2) - Before the recent downturn, China’s housing market exhibited sensitivity to shifts in short-term interest rates: lower short-term borrowing costs were followed by accelerating house price growth. - Since the property sector downturn began in mid-2021, the relationship between house prices and borrowing costs has weakened; nonmonetary factors (developer distress, large inventories of unfinished homes) now play a more significant role. - Transmission to consumption via wealth and collateral channels is muted: - Preference for homeownership is associated with higher saving rates, muting wealth effects. - Restrictions on home equity credit and low regulatory mortgage loan-to-value limits—60 percent, which is close to the 10th percentile in a cross-country comparison (Figure 2.6)—further weaken the collateral channel. - Cash-flow channel: despite prevalence of floating interest rates, existing borrowers have seen limited benefits because benchmark reference rates have adjusted only modestly, reflecting limited use of interest-rate-based policy easing. - In the most recent property downturn and easing cycle, multiple rate cuts had only a limited impact on housing-related interest rates, prompting a one-time mortgage rate cut in September 2023. - Policy recommendation for China: increasing reliance on interest-rate-based tools (as opposed to greater reliance on credit policies) would help ensure more effective policy transmission via the housing channel. *Source: Excerpts and figures from Chapter 2 and its boxes in the April 2024 World Economic Outlook.* ### References ### References ### Selected references (excerpt) - Aastveit, Knut Are, and André K. Anundsen. 2022. “Asymmetric Effects of Monetary Policy in Regional Housing Markets.” American Economic Journal: Macroeconomics 14 (4): 499–529. https:// doi .org/ 10 .1257/ mac .20190011. - Aladangady, Aditya. 2017. “Housing Wealth and Consumption: Evidence from Geographically-Linked Microdata.” American Economic Review 107 (11): 3415–46. https:// doi .org/ 10 .1257/ aer .20150491. - Alam, Zohair, Adrian Alter, Jesse Eiseman, Gaston Gelos, Heedon Kang, Machiko Narita, Erlend Nier, and Naixi Wang. Forthcoming. “Digging Deeper—Evidence on the Effects of Macroprudential Policies from a New Database.” Published ahead of print, January 22, 2024. Journal of Money, Credit and Banking. https:// doi .org/ 10 .1111/ jmcb .13130. - Albuquerque, Bruno, Martin Iseringhausen, and Frederic Opitz. 2024. “The Housing Supply Channel of Monetary Policy.” IMF Working Paper 24/023, International Monetary Fund, Washington, DC. https:// www .imf .org/ en/ Publications/ WP/ Issues/ 2024/ 02/ 02/ The -Housing -Supply -Channel -of -Monetary -Policy -544046. - Altunok, Fatih, Yavuz Arslan, and Steven Ongena. 2023. “Monetary Policy Transmission with Adjustable and Fixed Rate Mortgages: The Role of Credit Supply.” Discussion Paper 18293, Centre for Economic Policy Research, London. https:// cepr .org/ publications/ dp18293. - Araujo, Juliana D., Manasa Patnam, Adina Popescu, Fabian Valencia, and Weijia Yao. 2020. “Effects of Macroprudential Policy: Evidence from over 6,000 Estimates.” IMF Working Paper 20/067, International Monetary Fund, Washington, DC. https:// doi .org/ 10 .5089/ 9781513545400 .001. - Battistini, Niccolò, Matteo Falagiarda, Angelina Hackmann, and Moreno Roma. 2022. “Navigating the Housing Channel of Monetary Policy across Euro Area Regions.” ECB Working Paper 2022/2752, European Central Bank, Frankfurt. - Bauer, Michael D., and Eric T. Swanson. 2023. “An Alternative Explanation for the ‘Fed Information Effect.’” American Economic Review 113 (3): 664–700. https:// doi .org/ 10 .1257/ aer .20201220. - Beraja, Martin, Andreas Fuster, Erik Hurst, and Joseph Vavra. 2019. “Regional Heterogeneity and the Refinancing Channel of Monetary Policy.” Quarterly Journal of Economics 134 (1): 109–83. https:// doi .org/ 10 .1093/ qje/ qjy021. - Berger, David, Konstantin Milbradt, Fabrice Tourre, and Joseph Vavra. 2021. “Mortgage Prepayment and Path-Dependent Effects of Monetary Policy.” American Economic Review 111 (9): 2829–78. https:// doi .org/ 10 .1257/ aer .20181857. - Bernanke, Ben S., and Mark Gertler. 1995. “Inside the Black Box: The Credit Channel of Monetary Policy Transmission.” Journal of Economic Perspectives 9 (4): 27–48. https:// doi .org/ 10 .1257/ jep .9 .4 .27. - Bernanke, Ben S., and Kenneth N. Kuttner. 2005. “What Explains the Stock Market’s Reaction to Federal Reserve Policy?” Journal of Finance 60 (3): 1221–57. https:// doi .org/ 10 .1111/ j .1540 -6261 .2005 .00760 .x. - Beyer, Robert C. M., Ezgi O. Ozturk, Claire Li, Florian Misch, Ruo Chen, and Lev Ratnovski. 2024. “Monetary Policy Pass-Through to Interest Rates: Stylized Facts from 30 European Countries.” IMF Working Paper 24/009, International Monetary Fund, Washington, DC. https:// www .imf .org/ en/ Publications/ WP/ Issues/ 2024/ 01/ 12/ Monetary -Policy -Pass -Through -to -Interest -Rates -Stylized -Facts -from -30 -European -Countries -543715. - Bhutta, Neil, and Benjamin J. Keys. 2016. “Interest Rates and Equity Extraction during the Housing Boom.” American Economic Review 106 (7): 1742–74. https:// doi .org/ 10 .1257/ aer .20140040. - Biljanovska, Nina, Sophia Chen, R. G. Gelos, Deniz O. Igan, Maria Soledad Martinez Peria, Erlend Nier, and Fabian Valencia. 2023. “Macroprudential Policy Effects: Evidence and Open Questions.” IMF Departmental Paper 23/002, International Monetary Fund, Washington, DC. https:// doi .org/ 10 .5089/ 9798400226304 .087. - Biljanovska, Nina, and Giovanni Dell’Ariccia. 2023. “Flattening the Curve and the Flight of the Rich: Pandemic-Induced Shifts in US and European Housing Markets.” IMF Working Paper 23/266, International Monetary Fund, Washington, DC. https:// www .imf .org/ en/ Publications/ WP/ Issues/ 2023/ 12/ 22/ Flattening -the -Curve -and -the -Flight -of -the -Rich -Pandemic -Induced -Shifts -in -US -and -European -542850. - Brandão-Marques, Luis, Gaston Gelos, Thomas Harjes, Ratna Sahay, and Yi Xue. 2020. “Monetary Policy Transmission in Emerging Markets and Developing Economies.” IMF Working Paper 20/035, International Monetary Fund, Washington, DC. https://www.imf.org/en/Publications/WP/ Issues/2020/02/21/Monetary-Policy-Transmission-in -Emerging-Markets-and-Developing-Economies-49036. - Burstein, Ariel, and Gita Gopinath. 2014. “International Prices and Exchange Rates.” In Handbook of International Economics, vol. 4, 391–451. Amsterdam: Elsevier. - Calza, Alessandro, Tommaso Monacelli, and Livio Stracca. 2013. “Housing Finance and Monetary Policy.” Journal of the European Economic Association 11 (S1): 101–22. https:// doi .org/ 10 .1111/ j .1542 -4774 .2012 .01095 .x. - Checo, Ariadne, Francesco Grigoli, and Damiano Sandri. 2024. “Monetary Policy Transmission in Emerging Markets: Proverbial Concerns, Novel Evidence.” BIS Working Papers 1170, Bank for International Settlement, Basel, Switzerland. https:// www .bis .org/ publ/ work1170 .htm. - Chen, Jiaqian, Daria Finocchiaro, Jesper Lindé, and Karl Walentin. 2023. “The Costs of Macroprudential Deleveraging in a Liquidity Trap.” Review of Economic Dynamics 51 (December): 991–1011. https:// doi .org/ 10 .1016/ j .red .2023 .09 .005. - Chodorow-Reich, Gabriel, Adam M. Guren, and Timothy J. McQuade. 2024. “The 2000s Housing Cycle with 2020 Hindsight: A Neo-Kindlebergerian View.” Review of Economic Studies 91 (2): 785–816. https:// doi .org/ 10 .1093/ restud/ rdad045. - Cloyne, James, Clodomiro Ferreira, and Paolo Surico. 2020. “Monetary Policy When Households Have Debt: New Evidence on the Transmission Mechanism.” Review of Economic Studies 87 (1): 102–29. https:// doi .org/ 10 .1093/ restud/ rdy074. - Corsetti, Giancarlo, João B. Duarte, and Samuel Mann. 2022. “One Money, Many Markets.” Journal of the European Economic Association 20 (1): 513–48. https:// doi .org/ 10 .1093/ jeea/ jvab030. - Deb, Pragyan, Harald Finger, Kenichiro Kashiwase, Yosuke Kido, Siddharth Kothari, and Evan Papageorgiou. 2022. “Housing Market Stability and Affordability in Asia-Pacific.” IMF Departmental Paper 22/020, International Monetary Fund, Washington, DC. https:// www .imf .org/ en/ Publications/ Departmental -Papers -Policy -Papers/ Issues/ 2022/ 12/ 13/ Housing -Market -Stability -and -Affordability -in -Asia -Pacific -513882. - Di Maggio, Marco, Amir Kermani, Benjamin J. Keys, Tomasz Piskorski, Rodney Ramcharan, Amit Seru, and Vincent Yao. 2017. “Interest Rate Pass-Through: Mortgage Rates, Household Consumption, and Voluntary Deleveraging.” American Economic Review 107 (11): 3550–88. https:// doi .org/ 10 .1257/ aer .20141313. - Eichenbaum, Martin, Sergio Rebelo, and Arlene Wong. 2022. “State-Dependent Effects of Monetary Policy: The Refinancing Channel.” American Economic Review 112 (3): 721–61. https:// doi .org/ 10 .1257/ aer .20191244. - Favilukis, Jack, Sydney C. Ludvigson, and Stijn Van Nieuwerburgh. 2017. “The Macroeconomic Effects of Housing Wealth, Housing Finance, and Limited Risk Sharing in General Equilibrium.” Journal of Political Economy 125 (1): 140–223. https:// doi .org/ 10 .1086/ 689606. - Flodén, Martin, Matilda Kilström, Jósef Sigurdsson, and Roine Vestman. 2021. “Household Debt and Monetary Policy: Revealing the Cash-Flow Channel.” Economic Journal 131 (636): 1742–71. https:// doi .org/ 10 .1093/ ej/ ueaa135. - Fonseca, Julia, and Lu Liu. 2023. “Mortgage Lock-In, Mobility, and Labor Reallocation.” SSRN Scholarly Paper, Rochester, NY. https:// doi .org/ 10 .2139/ ssrn .4399613. - Friedman, Milton. 1961. “The Lag in Effect of Monetary Policy.” Journal of Political Economy 69 (5): 447–66. https://www.jstor.org/stable/1828534. - Gorea, Denis, Oleksiy Kryvtsov, and Marianna Kudlyak. 2022. “House Price Responses to Monetary Policy Surprises: Evidence from the U.S. Listings Data.” Working Paper 2022–16, Federal Reserve Bank of San Francisco, San Francisco. - Gupta, Arpit, Vrinda Mittal, Jonas Peeters, and Stijn Van Nieuwerburgh. 2022. “Flattening the Curve: Pandemic-Induced Revaluation of Urban Real Estate.” Journal of Financial Economics 1462: 594–636. https:// doi .org/ 10 .1016/ j .jfineco .2021 .10 .008. - Hedlund, Aaron, Fatih Karahan, Kurt Mitman, and Serdar Ozkan. 2017. “Monetary Policy, Heterogeneity, and the Housing Channel.” Meeting Paper 1610, Society for Economic Dynamics. - Huang, Haifang, and Yao Tang. 2012. “Residential Land Use Regulation and the US Housing Price Cycle between 2000 and 2009.” Journal of Urban Economics 71 (1): 93–99. https:// doi .org/ 10 .1016/ j .jue .2011 .08 .001. - Iacoviello, Matteo, and Stefano Neri. 2010. “Housing Market Spillovers: Evidence from an Estimated DSGE Model.” American Economic Journal: Macroeconomics 2 (2): 125–64. https:// doi .org/ 10 .1257/ mac .2 .2 .125. - Igan, Deniz, and Prakash Loungani. 2012. “Global Housing Cycles.” Working Paper 12/217, International Monetary Fund, Washington, DC. - International Monetary Fund (IMF). 2022. “People’s Republic of China: Selected Issues: Household Savings and Its Drivers—Some Stylized Facts.” IMF Country Report 22/022, International Monetary Fund, Washington, DC. - Jordà, Òscar. 2005. “Estimation and Inference of Impulse Responses by Local Projections.” American Economic Review 95 (1): 161–82. - Jordà, Òscar, Moritz Schularick, and Alan M. Taylor. 2015. “Betting the House.” In “37th Annual NBER International Seminar on Macroeconomics,” Supplement, Journal of International Economics 96 (S1): S2–S18. - Kaplan, Greg, Kurt Mitman, and Giovanni L. Violante. 2020. “The Housing Boom and Bust: Model Meets Evidence.” Journal of Political Economy 128 (9): 3285–345. - Keynes, John Maynard. 1936. The General Theory of Employment, Interest and Money. London: Macmillan. - Kiyotaki, Nobuhiro, and John Moore. 1997. “Credit Cycles.” Journal of Political Economy 105 (2): 211–48. - Kuchler, Theresa, Monika Piazzesi, and Johannes Stroebel. 2023. “Housing Market Expectations.” In Handbook of Economic Expectations, edited by Rüdiger Bachmann, Giorgio Topa, and Wilbert Van der Klaauw, 163–91. Amsterdam: Elsevier. - Li, Wenli, and Yichen Su. 2023. “The Great Reshuffle: Residential Sorting during the COVID-19 Pandemic and Its Welfare Implications.” https:// papers .ssrn .com/ sol3/ papers .cfm ?abstract _id = 3997810. - Mian, Atif, Kamalesh Rao, and Amir Sufi. 2013. “Household Balance Sheets, Consumption, and the Economic Slump.” Quarterly Journal of Economics 128 (4): 1687–726. - Mian, Atif, and Amir Sufi. 2009. “The Consequences of Mortgage Credit Expansion: Evidence from the U.S. Mortgage Default Crisis.” Quarterly Journal of Economics 124 (4): 1449–96. https:// doi .org/ 10 .1162/ qjec .2009 .124 .4 .1449. - Mian, Atif, and Amir Sufi. 2018. “Finance and Business Cycles: The Credit-Driven Household Demand Channel.” Journal of Economic Perspectives 32 (3): 31–58. - Pica, Stefano. 2021. “Housing Markets and the Heterogeneous Effects of Monetary Policy across the Euro Area.” SSRN Scholarly Paper. - Saiz, Albert. 2010. “The Geographic Determinants of Housing Supply.” Quarterly Journal of Economics 125 (3): 1253–96. - Stock, James H., and Mark W. Watson. 2018. “Identification and Estimation of Dynamic Causal Effects in Macroeconomics Using External Instruments.” Economic Journal 128 (610): 917–48. - van Binsbergen, Jules H., and Marco Grotteria. 2023. “Monetary Policy Wedges and the Long-Term Liabilities of Households and Firms.” SSRN Scholarly Paper. - Wong, Arlene. 2019. “Refinancing and the Transmission of Monetary Policy to Consumption.” Unpublished, Princeton Economics, Princeton University, Princeton, NJ. ### Chapter 3 — Slowdown in global medium-term growth: key findings (excerpt) - Without timely policy interventions or a boost from emerging technologies, global growth will be only 2.8 percent by the end of the decade, significantly below its prepandemic (2000–19) average by a gap of 1 percentage point. - Expectations for medium-term (five-year-ahead) growth have been revised downward across all income groups and regions, most significantly in emerging market economies. - Actual growth has 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 that TFP growth could have been 50 percent higher if misallocation had not increased. - Most of the misallocation increase is because of 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 to lift productivity. - 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. - The chapter frames three core policy priorities to raise growth prospects: - Improve capital and labor allocation to more productive firms by addressing persistent structural frictions. - Enhance labor force participation. - Harness the potential of artificial intelligence. *Source: Excerpted references and chapter text from the IMF 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? ### Key takeaways and headline projections - Global labor supply growth is projected to be a mere 0.3 percent by 2030, less than a third of its average in the decade before the pandemic. - Based on projected demographic trends and conservative assumptions about technological progress, global growth in the medium term could fall below 3 percent. - Returning to the historical (2000–19) annual growth average of 3.8 percent requires growth-enhancing policies and reforms aimed to improve allocative efficiency, labor participation, cross-border trade and knowledge exchange, and innovation capabilities to maximize benefits from technological advances such as AI. - Five-year-ahead WEO growth projections show a broad-based downturn in growth prospects since 2008 that affects nearly 82 percent of economies. - 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. ### Insights from medium-term forecasts and convergence - The dimming medium-term outlook is aligned with projections of potential output growth; WEO medium-term forecasts are generally well aligned with projections of potential output growth. - There is no evidence of a forecaster pessimism bias when tracking the average discrepancy between forecast and realized growth (Online Annex Figure 3.1.1). - The catch-up efforts of emerging market and developing economies explain only about a quarter of the projected global growth decline since 2008. - Box 3.2 and related analysis suggest the pace of convergence in income and social welfare is slowing or potentially reversing over the medium term—contrasting with pre-pandemic historical trends. ### Drivers of the slowdown: TFP, capital, and labor - Total factor productivity (TFP) declines are the primary driver across country groups: - 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 has contributed significantly: - In OECD economies, business investment in 2021 fell by about 40 percent of its pre-global-financial-crisis trend. - Regression analysis indicates that 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. - Labor contribution has declined due to demographic change and retreat in labor force participation in major economies. ### Demographic trends and labor supply implications - Since 2008, growth in the working-age population (ages 15–64) has slowed in about 92 percent of the global economy and has been negative in about 44 percent. - Nearly two in every three new entrants over the medium term to the global workforce will come from India and sub-Saharan Africa. - Aggregate labor force participation rates declined between 2008 and 2021 in most world regions, with exceptions: Advanced Asia and the Pacific, the Middle East and North Africa, Europe, and Canada. - The pandemic exacerbated participation declines between 2019 and 2020, with some recovery in 2021, but participation remained broadly lower than in 2019: - Latin America participation declined about 1.9 percentage points. - United States participation lost about 1.4 percentage points. - Shift-share analysis findings: - Aging imposes a clear drag on participation in all advanced economies and China, and to a lesser extent in Latin America. - Advanced economies (except the United States) partially offset aging effects through significant within-group participation gains, driven by female participation and higher participation of older workers. - Emerging markets and the United States saw declines in male participation that dragged aggregate rates down. ### Policies associated with higher labor participation (OECD-based associations) - Estimated policy associations (change from 75th to 25th percentile where change enhances participation) suggest: - Reduced unemployment benefits and lower labor taxes are associated with higher participation for men ages 25 to 54. - Expansion in secondary education enrollment is associated with higher future participation for women ages 25 to 54. - Childcare programs and labor market programs (retraining and reskilling) are associated with higher female participation ages 25 to 54. - Retirement-age reforms and spending on labor market programs are associated with higher participation for older workers (ages 55 to 64). ### Firm-level and macro determinants of the investment decline - Net investment rates declined after 2008 in both advanced and emerging market economies (Figure 3.9). - Firm- and macro-level regression results align with theory: investment rates increase with Tobin’s q, profits, and cash stock; and decrease with higher corporate leverage and the cost of debt. - Magnitude of investment rate declines since 2008: - About 2.3 percentage points decline in the overall investment rate in advanced economies. - About 2 percentage points decline in emerging markets. - Explainable component of the decline: - More than half of the investment decline in advanced economies and virtually all of it in emerging markets can be explained by the included determinants. - Specific contributions and financial structure changes: - Tobin’s q decreased by 10 to 30 percent on average since 2008, contributing substantially to the explained decline in investment in both advanced and emerging market economies. - Emerging markets experienced an average 20 percent increase in leverage after 2008, contributing notably to the fall in investment rates. ### How growth shortfalls translated into investment shortfalls - Using narrative fiscal shocks as instruments for output growth (constructed for 21 OECD economies), the analysis links weaker economic activity to reduced investment: - Comparing with the precrisis trend, as of 2021, about half of the shortfall in OECD business investment since 2008 can be linked to weaker economic activity. ### Policy implications and what it will take to reverse the trend - Returning global growth to historical averages requires: - Strong policy support and reforms that improve allocative efficiency and labor participation. - Policies to facilitate cross-border trade and knowledge exchange. - Measures to enhance innovation capabilities and maximize the capacity to benefit from technological advances such as AI. - Specific policy levers suggested by empirical associations: - Labor-market reforms (including retirement-age reforms). - Expanded secondary education and childcare programs to raise female participation. - Labor market programs focused on retraining and reskilling. - Tax and unemployment benefit reforms that can encourage prime-age male participation. - Addressing investment shortfalls entails restoring firms’ expectations (Tobin’s q), reducing leverage constraints where necessary, and lowering uncertainty to revive capital formation. *Source: CHAPTER 3, "SLOWDOWN IN GLOBAL MEDIUM-TERM GROWTH: WHAT WILL IT TAKE TO TURN THE TIDE?" (text from IMF World Economic Outlook, April 2024).* ### Annex Figure 3.2.4). ### Annex Figure 3.2.4). ### Investment decline and uncertainty - The decline in GDP growth since 2008 helps explain the investment decline, even after key firm-level investment determinants are controlled for. - Rising uncertainty after 2008 makes a smaller but still significant contribution to the investment decline in advanced economies. - In emerging markets, increased capital inflows since 2008 have been positive for investment. ### Productivity and the role of resource misallocation - TFP growth has slowed over the past two to three decades. - Suggested contributors to the slowdown include: - Waning gains from information and communication technology. - Declining business dynamism. - Tighter credit conditions limiting new technology investments. - Slower expansion of cross-border capital flows and trade since 2008. - Allocative efficiency measures how well capital and labor are allocated to the most productive firms; a decline reduces TFP growth, while an improvement boosts it. - The approach used (Hsieh and Klenow (2009); Bils, Klenow, and Ruane (2021)) finds allocative efficiency declined during 2000–19 in most countries in a sample of 15 advanced and 5 emerging market economies. ### Quantified impacts of misallocation on TFP - The median country experienced an average annual drag on TFP growth of about 0.9 percentage point from declining allocative efficiency during 2000–19. - 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 this period, implying increased misallocation may have halved its TFP growth. - Exception: United States — improvements in allocative efficiency helped boost annual TFP growth by 0.8 percentage point over the period. ### Sectoral composition versus within-sector developments - Decomposition for 20 economies shows changing sector shares in GDP contributed only about 30 percent of the annual drag on TFP; the remainder is attributable to within-sector developments. - For China, the shift in sectoral GDP shares contributes 60 percent of the allocative-efficiency impact on TFP growth. - Service sectors display more inefficiency than goods-producing sectors, contributing to aggregate declines in allocative efficiency as economies shift from goods to services. ### Firm-level productivity dispersion and dynamics - Dispersion of firms’ real productivity in the 20 sample economies rose significantly leading up to the global financial crisis and, despite some reversion, remains elevated. - A widening distribution of firms’ real productivity raises misallocation because frictions slow capital and labor reallocation to faster-growing firms. - Sector-level evidence: a rise in a sector’s dispersion of real firm productivity is accompanied by a decline in its allocative efficiency. ### Transitory versus structural components of misallocation - Recovery of allocative efficiency after shocks is slow: it takes 9–11 years for allocative efficiency to return halfway to its long-term fundamental level. - For the analyzed economies, about one-third of measured misallocation is attributable to transitory factors, and two-thirds has structural roots. - Cross-country variation in structural allocative efficiency correlates with market entry and competition, trade openness, financial access, and labor market flexibility. - If countries with allocative efficiency below the United States reduced their gaps in structural policies by 15 percent over 10 years, it could boost medium-term TFP growth by 0.7 percentage point. ### Medium-term growth baseline (to 2030) - Projection method: labor force participation forecasts use a cohort-based approach with United Nations demographic projections; capital growth merges WEO public investment forecasts with chapter estimates of medium-term private investment; TFP growth assumes sectoral allocative efficiency moves toward its long-term level reaching its half-life in the medium term and efficient TFP follows the historical trend. - Labor: - 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: - Low-income countries: 2.1 percent projected growth in labor supply. - Emerging market economies, excluding China: 0.9 percent growth. - United States: 0.5 percent growth. - China: labor supply projected to contract by 0.6 percent. - EU: labor supply projected to contract by 0.5 percent. - 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. - Continued high public debt likely constrains future public investment in emerging market and developing economies, which accounts for 30 percent of these countries’ overall capital. - Advanced economies expected to see a modest increase in public investment, but its growth impact will be minimal given its small share in overall investment. - Private investment rates expected to remain low in both country groups. - TFP: - 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. - Causes for slower efficient TFP growth: 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 outcome: - World growth rate projected at 2.8 percent in 2030 under the baseline scenario. - Historical (2000–19) annual average was 3.8 percent. ### Alternative scenarios and policy levers - Range of medium-term growth effects relative to the baseline: from 1.2 percentage points above to 0.8 percentage point below the baseline. - Scenarios considered include: - Policies to increase labor force participation (assumes countries increase participation rates by 3.2 percentage points, the median increment if all countries converged to the best policies). - Migration boosts to advanced economies’ labor supply. - Structural reforms reducing misallocation. - Policies improving allocation of talent in emerging market and developing economies. - Wide adoption of artificial intelligence (AI). - Persistent public debt overhang. - Geoeconomic fragmentation (“fragmentation”). - Larger effects are possible if scenarios occur simultaneously; estimates are indicative and subject to high uncertainty. *Source: Annex Figure 3.2.4).* ### 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? ### Scenario impacts on global growth - Labor supply boost from higher labor force participation among older workers: increase labor supply growth by about 0.3 percentage point, contributing 16 basis points to global growth. - Migration boost to labor supply in advanced economies: assumes 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 improving allocative efficiency: closing 15 percent of the policy gap with the United States (product and labor market policies, trade openness, financial deepening) 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: aligning talent allocations with the United States’ trend could boost global growth by a quarter of a percentage point. - AI technologies: 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 under simulated scenarios. - Geoeconomic fragmentation: scenarios of heightened trade barriers and “friend-shoring” reduce growth by 10 basis points in limited cases up to 80 basis points in more extensive reshoring scenarios. ### Key findings on drivers of the slowdown - A significant slowdown in TFP is identified as a key factor behind declining actual growth and waning growth expectations; this slowdown is driven by increased resource misallocation and slower growth in efficient TFP. - Demographic pressures: a shrinking working-age population in major economies has contributed to slower medium-term growth. - Investment: lackluster business investment has also been a material contributor to the slowdown. - The chapter emphasizes that regaining historical growth will demand substantial policy efforts and potentially net positive benefits from AI; structural reforms to resolve misallocation are central. ### Policy recommendations - Prioritize reforms that 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. - Complement structural reforms with governance and external sector reforms. - Avoid poorly designed industrial policies that may impede resource allocation to more productive firms or sectors. - Facilitate migration and labor integration: policies to ease flow and integration of migrant workers and measures to boost labor force participation among older workers in advanced economies (through retirement reforms and labor market programs). - Expand women’s participation in emerging market economies by increasing education enrollment and childcare support, and reduce social barriers and gender discrimination to improve talent allocation. - Invest in human capital in low-income developing countries to leverage demographic dividends. - Reform corporate restructuring and insolvency mechanisms and eliminate debt bias in corporate tax policies to support capital formation and business investment in emerging market economies. - Steer clear of damaging unilateral trade and industrial policies to lessen negative growth impacts from geoeconomic fragmentation. - Strengthen regulatory frameworks for AI, including intellectual property protection, and revisit redistributive and adjustment programs to ensure AI benefits are shared fairly and widely. - Promote innovation-focused policies to influence long-run global growth paths. ### Allocative efficiency: concept and measurement (Box 3.1) - Allocative efficiency: how well allocation of capital and labor across firms reflects relative productivity; misallocation can depress average TFP. - Hsieh and Klenow (2009) approach: measures allocative efficiency indirectly by comparing marginal revenue product of capital and labor across firms; dispersion in marginal revenue productivity implies misallocation. - Frictions causing misallocation include size-dependent tax, labor, and social insurance policies; informality and corruption; weak property rights; regional barriers; restrictive trade policies; uneven firm markups; and financial frictions. - Country case studies show policy levers to reduce misallocation, such as removing barriers to international trade and credit-access reforms. ### Distributional implications of the medium-term slowdown (Box 3.2) - Between-country convergence slowed: convergence was sustained during 2008–19 but 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. - Projections combining within-country and between-country inequality from the WEO show either no or only modest expected recoupment in the medium term. - Welfare vs GDP: welfare growth (lifetime expected utility including consumption, life expectancy, leisure, inequality) historically exceeded GDP growth; both GDP and welfare growth are predicted to fall postpandemic, with welfare growth deteriorating more than GDP growth. - AI effects: expected skewed effect of AI on growth would increase between-country divergence unless other factors improve within-country income distribution or welfare dimensions like life expectancy. ### Artificial intelligence: exposure, complementarity, and modeled scenarios (Box 3.3) - Disparities in AI exposure by country group: - approximately 60 percent of jobs in advanced economies are susceptible to changes from 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 exposed jobs; the other half could face automation risks reducing labor demand and wages. - Model channels for AI effects: labor displacement, AI complementarity with skills, and productivity gains that boost investment and labor demand. - Two modeled scenarios (calibrated to the United Kingdom): - High complementarity scenario: AI use leads output to increase by almost 10 percent as the economy adjusts through capital deepening and a small increase in total factor productivity. - High complementarity and high productivity scenario: output expands by 16 percent and total factor productivity increases by almost 4 percent, with gains occurring primarily in the first decade of transition. - Overall estimated medium-term global growth impact of AI ranges from 10 to 80 basis points depending on adoption and whether AI replaces or augments workers. *Source: CHAPTER 3 SLOWDOWN IN gLObaL MEDIUM-TERM gROWTH: WHaT WILL IT TaKE TO TURN THE TIDE?, International Monetary Fund | April 2024.* ### Box 3.3. The Potential Impact of Artificial Intelligence on Global Productivity and Labor Markets ### Box 3.3. The Potential Impact of Artificial Intelligence on Global Productivity and Labor Markets ### Projected distributional effects on wages and inequality - Wages 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. - Advanced-economy worker composition: 27 percent of workers occupy high-exposure and high-complementarity occupations. - Emerging-market worker composition: 16 percent of workers occupy high-exposure and high-complementarity occupations. - Low-income-country worker composition: 8 percent of workers occupy high-exposure and high-complementarity occupations. ### Productivity gains: country and global estimates - United Kingdom: Productivity gains from AI are expected to range from 0.9 to 1.5 percent a year, attributed to robust digital infrastructure, skilled labor force, innovation ecosystem, and regulatory framework. - Many emerging market and developing economies: Potential gains are less than half those estimated for the United Kingdom. - Global economy: Estimates suggest that AI could boost productivity gains by 0.1 percent to 0.8 percent annually over a decade. ### Mechanisms and factors driving disparities - The variance in potential AI benefits across countries stems largely from the initial distribution of workers across occupations (high-exposure and high-complementarity roles). - Countries with fewer workers in these occupations have reduced potential to realize AI-driven productivity gains. - The uneven geographic distribution of AI readiness underscores differences in digital infrastructure, skills, innovation ecosystems, and regulatory frameworks. ### Implications and policy directions - Uneven distribution of AI gains across regions underscores the need for international cooperation to improve AI readiness and integration in less-prepared nations. - Initiatives to improve AI preparedness can help reduce global inequalities and ensure that AI benefits reach a wider array of nations. ### Modeling and evidence notes - The figure referenced (Figure 3.3.2) shows the change in TFP and output between the initial and final steady state for the United Kingdom; model details are in Rockall, Pizzinelli, and Tavares 2024. - Sources informing the assessment include Cazzaniga and others 2024; and IMF staff calculations. *Source: Box 3.3, Chapter 3, World Economic Outlook (April 2024), International Monetary Fund.* ### CHAPTER 4 TRaDINg PLaCES: REaL SPILLOvERS FROM g20 EMERgINg MaRKETS ### CHAPTER 4 TRaDINg PLaCES: REaL SPILLOvERS FROM g20 EMERgINg MaRKETS ### Overview and methods - Firm-level microdata are used to estimate the effect of domestic growth surprises in G20 EMs on firm turnover in trading partners over the near to medium term, distinguishing: - output linkages: firms’ dependence on demand from G20 EMs for their products; and - input linkages: firms’ use of intermediate inputs from G20 EMs. - A multicountry, multisector model is used to explore longer-term spillovers from productivity shocks in G20 EMs, tracking reallocation of production across sectors and countries in steady-state scenarios, including shocks concentrated in GVC-intensive sectors and country-specific sectors (for example, construction in China). - A model-based simulation assesses whether positive growth surprises in other G20 EMs (excluding China) could support global growth in the face of weak growth prospects in China. ### Key findings on the rising footprint of G20 EMs - G20 EMs’ global trade and investment footprint has almost doubled since the early 2000s. - G20 EM consumers and firms account for a growing share of global demand, and firms in G20 EMs (for example, China, India, and Russia) supply a larger share of total inputs globally. - G20 EMs are among the largest producers of key commodities critical for the green transition (for example, Argentina for lithium and Indonesia for nickel), and other G20 EMs play important roles beyond China. - Deeper integration means G20 EMs increasingly resemble advanced economies: - output fluctuations have become less volatile and driven more by domestic shocks; - in some cases, G20 EMs can influence global prices. ### Magnitudes and patterns of spillovers - Growth spillovers from some G20 EMs can explain almost 5 percent of GDP variation in advanced economies. - China is the largest source of spillovers: its domestic shocks can explain about 10 percent of the variation in GDP in other emerging markets. - Other G20 EMs have important regional spillovers (examples cited: Russia in the Middle East and Europe; Mexico in Latin America). - Aggregate VAR and structural model estimates (2001–2023) show: - A 1 percentage point demand shock in China leads to an increase of about 0.3 percentage point in growth after three years in other emerging markets. - A 1 percentage point supply shock in China leads to an increase of about 0.15 percentage point in growth after three years in other emerging markets. - Effects on advanced economies are smaller. ### Firm- and sector-level transmission through GVCs - Following a positive shock in G20 EMs, firms with greater dependence on demand from G20 EMs (output linkages), especially if located in emerging markets, tend to experience faster revenue growth than other firms. - Firms that rely more on inputs supplied by G20 EMs (input linkages) tend to experience negative spillovers from positive G20 EM shocks. - Positive growth surprises in G20 EMs such as China and Mexico could be associated with expansion of competing production in trading partners, potentially displacing existing activity. - Over time, spillovers transmitted through GVCs have grown, with notable sectoral heterogeneity: - In a scenario where productivity shocks are concentrated in GVC-intensive sectors, most sectors shrink—particularly those in Asia—while some manufacturing sectors (for example, electronics and textiles) expand as economies take advantage of the decrease in supply from G20 EMs. ### Longer-term and scenario results - Negative productivity shocks in G20 EMs generally produce negative global spillovers through the trade channel, but can generate positive spillovers for some sectors and economies. - Spillovers from G20 EM productivity shocks have increased almost threefold since the early 2000s. - If all G20 EMs experience a productivity growth slowdown, Asia is the hardest-hit region, with intensity driven by its strong links to China. - In terms of employment: - Positive shocks from G20 EMs can lead to job losses in some sectors through increased competition. - Spillovers that propagate through sectors connected via GVCs tend to generate complementarities and more job opportunities. ### Financial and commodity linkages (selected quantitative facts) - Foreign direct investment (FDI) from G20 EMs increased from about 6 percent of total FDI in 2005 to about 10 percent just before the pandemic. - Lending from banks in the Group of Five (G5) to G20 EMs nearly doubled since the early 2000s, peaking at more than 2.5 percent of G5 economies’ GDP in 2014 and then gradually declining; lending to China drove the increase, followed by Brazil and India. - For comparison, goods trade with G20 EMs accounted for 8.1 percent of the total GDP of the G5 economies in 2022. - G20 EM portfolio liabilities to the G5 increased between 2001 and 2021 from 2.9 percent to 5.3 percent of the sender countries’ total portfolio claims—equivalent to 4.6 percent of G5 GDP in 2021. - G20 EM portfolio assets to the rest of the world were just over 2.5 percent of total cross-border portfolio assets as of 2021. ### Policy implications and recommendations - Policymakers should recognize that G20 EMs as a group—beyond China alone—are an important and growing source of global and regional spillovers. - Countries with strong linkages to G20 EMs should: - build appropriate buffers and policy frameworks to insure against transmission of negative shocks and potential external risks; - consider diversifying output and input linkages given the degree of reallocation in activity across sectors in response to G20 EM shocks; and - pursue domestic structural policies to avoid large-scale dislocation of production factors and promote efficient reallocation of those factors. - Policymakers should refrain from adopting protectionist policies that are detrimental to the domestic economy and can generate negative cross-border spillovers. *Source: CHAPTER 4 TRaDINg PLaCES: REaL SPILLOvERS FROM g20 EMERgINg MaRKETS, International Monetary Fund | April 2024* ### 2. Historical Decomposition of Real GDP Growth of G20 EMs ### 2. Historical Decomposition of Real GDP Growth of G20 EMs ### Lower volatility in G20 EMs - Real GDP growth volatility is computed as the within-country standard deviation of real GDP growth over a rolling 10-year window (value for 2000 refers to 2000–09). - Chart plots averages of real GDP growth volatility for advanced economies and G20 EMs (see Figure 4.1 for G20 EM list). - Source data: Penn World Table (version 10.1); IMF staff calculations. ### Aggregate spillovers: China versus other G20 EMs - Domestic growth shocks in China explain just under 5 percent of output variation in advanced economies after three years and just over 10 percent of that in other emerging markets. - In relative terms, growth spillovers from China to emerging markets are broadly similar in size to those from the United States. - Demand shocks in other G20 EMs account for less than 4 percent of GDP fluctuations in other countries. - A 1 percentage point increase in GDP in China leads to commodity prices that are almost 10 percent higher after one year and about 5 percent higher after three years; demand shocks in other G20 EMs do not significantly move commodity prices (Figure 4.7, panel 2). - China’s aggregate demand shocks were the major driver of spillovers from G20 EMs until the mid-2010s. - Aggregate supply shocks in China associated with expansion of productive capacity and export orientation after WTO accession; more recently associated with slowing productivity and a shrinking labor force. ### Relative contribution of G20 EMs over time - Within the G20 sample, the relative contribution of G20 EMs in explaining output fluctuations increased between the 2000s and the 2010s more than that of G20 advanced economies. - For an increasing number of countries, spillovers from G20 advanced economies and emerging markets (excluding China and the United States) are now broadly comparable (Figure 4.7, panel 3). ### Regional spillovers - Spillovers from China generally dominate those from other emerging markets, especially in Asia and to a lesser extent in Latin America (Figure 4.8). - Among other G20 EMs: - Russia and Türkiye generate significant regional spillovers in Europe and central Asia. - Domestic supply-side shocks in Brazil and Mexico impact Latin America via trade and commodity linkages. - Regional spillovers from Russia have manifested clearly since the invasion of Ukraine through disruptions in energy prices and grain markets. - Shocks in large emerging markets—and particularly China—have sizable cross-border implications for economies in sub-Saharan Africa and for low-income countries via commodity and demand channels. ### Spillovers from trade and global value chains (GVCs) - Two complementary approaches: firm-level analysis with input-output tables; quantitative trade model with input-output data to study sectoral TFP shocks. - Firm-level findings: - A 1 percentage point unexpected increase in GDP growth in G20 EMs leads to almost half a percentage point higher revenue growth after one year for firms more exposed to G20 EMs; effect fades but remains one-half of the initial level after five years (Figure 4.9, panel 1). - Effect is about half the size of similar spillovers from an unanticipated increase in growth in G20 advanced economies. - For firms headquartered in other emerging markets, revenue growth is 0.8 percentage point higher after five years for firms with greater exposure. - Positive spillovers are large for firms in export-dependent industries both on impact and after three years (Figure 4.9, panel 2). - Firms dependent on intermediate goods from G20 EMs appear overall unaffected by domestic growth surprises in G20 EMs (offsetting channels: cheaper supplies vs. increased competition). - For shocks from Indonesia and Türkiye, cheaper supply channel may dominate. For shocks from China, India, Mexico, competition channel seems to dominate, with downstream spillovers turning negative (revenue growth slowing by about 0.1 percentage point more for firms more exposed). - Trade-model (multisector input-output) scenarios (static, steady-state comparisons): - Baseline: negative shock equal to 2.5 percent of TFP hits all sectors in all G20 EMs (corresponding to a domestic output decline of about 10 percent). - Scenario 2: same TFP shock only to sectors in G20 EMs that are integrated into GVCs. - Scenario 3: case study—construction sector in China shocked. - Baseline model results: - Global GDP excluding G20 EMs declines by about 0.15 percent; about one-half of this decline is attributable to China, followed by India, Russia, and Mexico (Figure 4.10, panel 1, leftmost bar). - Applying same shocks to US productivity yields a global impact excluding the United States about one-third of the magnitude of the China shock. - Calibrating the baseline with trade and input-output data from 2000 shows spillovers in 2018 were almost three times larger than in 2000 (Figure 4.10, panel 1, middle bar). - Spillovers from the United States have remained broadly similar or slightly diminished over time. - Model spillovers are smaller than short-term aggregate demand/supply shock estimates because the model focuses on long term and the trade channel. - Scenario 2 (GVC-intensive sectors only): - Impact on global GDP outside G20 EMs is about two-thirds of baseline despite a domestic impact on G20 EMs about one-third as large (Figure 4.10, panel 1, rightmost bar). - Applying same shock to GVC-intensive sectors in the United States generates even smaller spillovers relative to those from shocks in G20 EMs. - Decomposition across regions (baseline, 2018): - Asian economies significantly affected, with TFP shocks from China dominating; India also contributes significantly. - Rest of the world region (includes most low-income developing countries and makes up about 10 percent of global GDP) is even more affected; India plays an important role for this region due to shocks in coke and refined petroleum products and basic metals. - Spillovers from other G20 EMs tend to be regional, consistent with short-term findings. - Europe tends to be most insulated; its impact driven more by shock to Russia. - For the Americas, shocks from China are largest contributor; shocks from Mexico are also important, particularly in Central and North America. - Sectoral reallocation (baseline): - Most sectors contract—agriculture, mining, utilities, and trade and services, especially in Asia—as trade slows (Figure 4.11, panel 1). - Most manufacturing sectors contract less; some manufacturing sectors expand (textiles, basic metals, electrical equipment). - Scenario 2 amplifies reallocation: standard deviation of changes in global sectoral value added outside G20 EMs increases by nearly one-third; number of sectors expanding increases from 5 to [text truncated in source]. ### Notes on methodology and data sources - Aggregate domestic shock contributions derived as weighted averages of sum of contributions of domestic aggregate demand and supply shocks estimated via country-specific structural vector autoregressions; contributions of foreign shocks derived as residuals (Figure 4.1 lists G20 EMs). - Firm-level analysis uses local projection methods; data sources include Eora Global Supply Chain Database and Orbis. - Trade-model calibration sources: Bonadio and others 2021, 2023; Huo, Levchenko, and Pandalai-Nayar (forthcoming); OECD Inter-Country Input-Output Tables; IMF staff calculations. - Confidence interval reporting: weighted averages use significance on basis of 68 percent credible intervals; firm-level significance noted at the 90 percent level where applicable. *Source: WORLD ECONOMIC OUTLOOK—STEaDy bUT SLOW: RESILIENCE aMID DIvERgENCE, International Monetary Fund | April 2024* ### 15. In this scenario, most manufacturing sectors ### 15. In this scenario, most manufacturing sectors ### Scenario: Productivity shock to Chinese construction and sectoral responses - A 2.5 percent productivity shock to the construction sector in China: - generates a 6 percent contraction in the value added of that sector in China. - generates a half percent contraction in other sectors in China’s economy. - Global sectoral impacts driven by this scenario: - Largest declines in sectoral value added occur in the production of energy commodities, particularly in mining, indicative of upstream propagation to inputs to the Chinese construction sector. - Air and water transportation also contract. - Textiles production expands significantly. - Electrical equipment production expands, pointing to domestic downstream linkages in China propagating to other economies through higher prices in downstream sectors in which China is an important player in GVCs. - Interpretation and mechanisms: - Upstream propagation: reduced Chinese construction demand lowers inputs (energy commodities, mining), and related transport services. - Downstream propagation: higher prices in downstream sectors where China is important in GVCs induce expansion of textiles and electrical equipment elsewhere. - The correlation between change in sectoral value added and change in prices shows the role of the price signal in inducing sectoral reallocation. ### Alternative scenario summary (G20 EMs GVC sectors) - In a scenario where supply from competing firms in G20 EMs decreases: - Most manufacturing sectors expand (examples: textiles, metals, electronics) as domestic firms take advantage of decreased supply from competing firms in G20 EMs. - Decline in production of basic commodities and expansion of textiles in this scenario are driven by emerging market and developing economies. - Expansion of manufacturing sectors and decline in services are concentrated in advanced economies, reflecting their more advanced technologies and larger share of the global economy. - Model sensitivity note: - Halving the trade elasticity from four to two delivers significantly less short-term expansion in sectoral value added, along both the intensive and extensive margins. ### Spillovers to sectoral employment - Methodology: - Consideration of spillovers from positive sectoral TFP shocks in any G20 economy-sector pair; employment increases where sectoral activity comoves positively and decreases where activity comoves negatively. - Catalog of economy-sector pairs in the G20 with largest positive (“complementarity”) and negative (“competition”) employment spillovers summarized in Table 4.1. - Key patterns: - Positive sectoral productivity shocks in G20 economies tend to: - increase employment in other foreign sectors along the global value chain, and - displace jobs in the same sectors abroad. - Manufacturing sectors in G20 EMs (notably China) are an important source of positive spillovers for one another; positive spillovers from advanced economies to emerging markets in these sectors are less widespread. - Notable source sectors and affected destinations (summary highlights from Table 4.1): - For advanced economies, largest positive employment spillovers from G20 EMs (mostly China) tend to emanate from: - computer, electronic, and optical equipment and textiles. - For emerging markets, additional job opportunities arise from positive shocks in: - basic metals, machinery, and energy commodities (predominantly China and Saudi Arabia). - For advanced economies, positive employment spillovers between advanced economies are driven by shocks to: - services (financial and insurance activities; professional, scientific, and technical activities from the United States) and manufacturing (motor vehicles from Germany and the United States). - Negative employment spillover patterns: - Services and higher-tech manufacturing in advanced economies are most negatively exposed to positive shocks in G20 EM sectors. - Agriculture and relatively low-tech manufacturing (such as textiles) are at highest risk of job losses in emerging markets. - China emerges as a key source of both positive and negative spillovers. - Additional methodological notes: - Sample covers 19 countries (all G20 economies excluding Australia), four regional aggregates, and a rest of the world aggregate; entries in Table 4.1 sum to 57 = 19 economies × 3 sectors. ### Can the Other G20 Emerging Markets Support Global Growth? - GIMF upside scenario design: - Uses IMF’s Global Integrated Monetary and Fiscal (GIMF) model augmented with an aggregate representation of GVCs. - Constructs positive short-term five-year aggregate demand and supply shocks—to household consumption and private investment—for each of the G20 EMs excluding China. - Shock size calibrated to capture a plausible upside to the WEO baseline: specifically, a 30 percent probability that growth in each G20 EM simultaneously could be higher than in this scenario. - Simulation outcomes: - Positive shocks raise aggregate GDP growth for the other G20 EMs by 0.7 percentage point over the WEO forecast horizon. - Global growth accelerates by half a percentage point. - About 85 percent of the global growth impact is driven by the size of the shocks; the remaining 15 percent results from spillovers onto one another, China, and advanced economies. - Regional and country patterns: - Spillovers on growth exceed 0.1 percentage point for the first few years in China. - In advanced economies, spillovers are less than 0.1 percentage point per year and are two-thirds the size of the impact on growth in China. - For advanced economies, spillovers originate mostly in energy exporters and Mexico. - Spillovers between emerging markets are larger and account for 13 percent of their growth pickup. - Upside shocks in India play a prominent role through GVCs and as a source of additional demand. ### Conclusions and Policy Implications - General implications: - Stronger global integration through trade and GVCs means domestic shocks in G20 EMs can drive larger spillovers to the global economy—sometimes comparable in size to spillovers from advanced economies—and generate employment gains and losses through reallocation across sectors and economies. - Deeper geoeconomic fragmentation could reduce cross-country diversification, increase macroeconomic volatility, amplify regional spillovers within blocs, and increase price volatility for key commodities. - Policy implications for domestic frameworks: - Need to design sound domestic macroeconomic policies to build buffers over the medium term against negative spillovers (for advanced and other emerging market and developing economies) and to manage domestic shocks (for G20 EMs). - G20 EMs should continue to strengthen monetary, fiscal, and financial frameworks and assess their impact on other economies. - Country-specific priorities could include: - strengthening fiscal positions to provide buffers; - reducing current account deficits to minimize external vulnerabilities; - reducing balance sheet vulnerabilities to ensure financial stability. - Policies to manage sectoral reallocation: - Pursue policies that take advantage of new opportunities and mitigate effects on sectors and firms exposed to negative spillovers. - Prioritize well-calibrated packages of structural reforms to sustain growth even when fiscal space is limited; reforms could cover governance, the external sector, labor markets, and business regulation. - Target policies to sectors that stand to benefit most from reallocation. - Use industrial policies, including large-scale subsidies or export restrictions, only amid large market failures or externalities because they can deepen fragmentation through adverse cross-border spillovers. - Avoid protectionist measures to insulate domestic sectors from foreign competition, as these can trigger retaliation and generate welfare losses. - Support sectors and firms hit by negative spillovers with inclusive policies, such as targeted fiscal support that facilitates efficient reallocation of labor, skills upgrades, adaptation to increased competition from emerging markets, and mitigation of harmful distributional impacts. - Promote competition to prevent increases in market power and improve access to credit for viable firms to foster reallocation. - Multilateral cooperation: - Strengthening the global financial safety net would allow timely and effective responses to the costs of negative cross-border spillovers. - Effective multilateral cooperation and international policy coordination are needed to manage spillovers and minimize fragmentation risks. ### Box: Domestic subsidies in G20 EMs and trade impacts (summary) - Empirical observations: - The number of subsidies has more than tripled during the past decade in G20 EMs. - By 2022, about 6,000 policies entailing domestic subsidies were in force in G20 EMs alone (Global Trade Alert database). - Effects of domestic subsidies on exports (difference-in-differences and gravity model results): - Intensive margin: exports of subsidized products grow faster over the eight years following the introduction of the subsidy; at that time, changes in exports of these products are about 10 percent higher than those of other products. - Extensive margin: domestic subsidies increase the probability of a product being exported by 3 percentage points relative to other products. - Gravity model: subsidies increase international trade relative to domestic sales. - Policy takeaway: - Domestic subsidies in G20 EMs can alter comparative advantage patterns and affect export dynamics. - Because such measures can have strong trade spillovers, international cooperation is needed to attenuate the possibility of a subsidy war through tit-for-tat behavior. *Source: International Monetary Fund, World Economic Outlook—Steady but Slow: Resilience amid Divergence (April 2024), Chapter 4.* ### 1. Domestic Subsidies in Force in ### 1. Domestic Subsidies in Force in ### Scope and definition - Subsidies are defined as government measures that involve a financial transfer and create an advantage for the beneficiaries. - Data exclude measures classified as export subsidies and include only measures that are classified as “distortive” (discriminating against foreign interests). - Panel 1 reports the number of such subsidies in G20 countries (chart axes shown from 0 to 7,000 and a year marker "2009"). ### Effects on exports (levels and probabilities) - Panel 2 reports the effect of domestic subsidies on exports in log points; the vertical scale shown runs from −0.2 to 0.6. - Panel 3 reports the effect of domestic subsidies on the probability of exports in percentage points; the vertical scale shown runs from −2 to 12. - Panels 2 and 3 plot the estimates and 90 percent confidence intervals on the subsidy dummy interacted with periods before and after the treatment (years shown relative to the implementation of subsidies from −12 to 12). ### Sample, specification, and controls - The sample for panels 2 and 3 includes G20 EMs. - The empirical specification includes: - dummies for other policies, - country-product fixed effects, - country-product linear time trends, - product-year fixed effects, - country-ISIC 2-digit-year fixed effects. - The charts display the timing of estimated effects relative to the implementation of subsidies (pre- and post-treatment periods). ### Key methodological notes - Estimates are plotted with 90 percent confidence intervals. - AEs = advanced economies; EMs = emerging markets. - The figure references Figure 4.1 for a list of G20 EMs. *Sources: Global Trade Alert database; Rotunno and Ruta 2024; and IMF staff calculations.* ### CHAPTER 4 TRaDINg PLaCES: REaL SPILLOvERS FROM g20 EMERgINg MaRKETS ### CHAPTER 4 TRaDINg PLaCES: REaL SPILLOvERS FROM g20 EMERgINg MaRKETS ### Statistical Appendix — Key Assumptions and Scope - Data in the statistical tables have been compiled on the basis of information available through April 1, 2024. - The figures for 2024–25 are shown with the same degree of precision as the historical figures solely for convenience; because they are projections, the same degree of accuracy is not to be inferred. - Real effective exchange rates for the advanced economies are assumed to remain constant at their average levels measured during January 30, 2024–February 27, 2024. - Assumed average US dollar–special drawing right conversion rates: 1.329 (2024) and 1.331 (2025). - Assumed US dollar–euro conversion rates: 1.078 (2024) and 1.073 (2025). - Assumed yen–US dollar conversion rates: 148.5 (2024) and 146.4 (2025). - Oil price assumptions: $78.61 a barrel in 2024 and $73.68 a barrel in 2025. - Policy assumption: national authorities’ established policies are assumed to be maintained. - Interest-rate assumptions (three-month government bond yield): - United States: 5.2 percent (2024) and 4.1 percent (2025). - Euro area: 3.5 percent (2024) and 2.6 percent (2025). - Japan: 0.0 percent (2024) and 0.1 percent (2025). - Interest-rate assumptions (10-year government bond yield): - United States: 4.1 percent (2024) and 3.7 percent (2025). - Euro area: 2.5 percent (2024) and 2.6 percent (2025). - Japan: 1.0 percent (2024) and 1.1 percent (2025). ### What’s New (Database and Publication Changes) - Ecuador’s fiscal sector projections are excluded from publication for 2024–29 because of ongoing program discussions. - Vietnam has been removed from the Low-Income Developing Countries (LIDCs) group and added to the Emerging Market and Middle-Income Economies (EMMIEs) group. - For West Bank and Gaza, data for 2022–23 previously excluded from publication pending methodological adjustments to statistical series are now included; projections for 2024–29 are excluded from publication on account of the unusually high degree of uncertainty. ### Data Bases, Standards, and Aggregation Conventions - Data and projections for 196 economies form the statistical basis of the WEO database. - Most countries’ macroeconomic data as presented in the WEO conform broadly to the 2008 version of the System of National Accounts (SNA 2008). - IMF sector statistical standards referenced: Balance of Payments and International Investment Position Manual (BPM6), Monetary and Financial Statistics Manual and Compilation Guide, and Government Finance Statistics Manual 2014 (GFSM 2014), aligned with SNA 2008. - Fiscal gross and net debt data are drawn from official data sources and IMF staff estimates; attempts are made to align with GFSM 2014 but deviations can occur due to data limitations or country circumstances. - Composite construction and weighting conventions: - Country group composites for exchange rates, interest rates, and growth rates of monetary aggregates are weighted by GDP converted to US dollars at market exchange rates (averaged over the preceding three years) as a share of group GDP. - Composites for other domestic-economy data (growth rates or ratios) are weighted by GDP valued at purchasing power parity as a share of total world or group GDP. - For aggregation of inflation: world and advanced economies use simple percent changes from the previous years; emerging market and developing economies use logarithmic differences. - Arithmetically weighted averages are used for all data for the emerging market and developing economies group—except data on inflation and money growth, for which geometric averages are used. - Composites for real GDP per capita in purchasing-power-parity terms are sums of individual country data after conversion to international dollars in the years indicated. - Composites for fiscal data are sums of individual country data after conversion to US dollars at the average market exchange rates in the years indicated. - Composites relating to external sector statistics are sums of individual country data after conversion to US dollars at the average market exchange rates in the years indicated for balance of payments data and at end-of-year market exchange rates for debt denominated in currencies other than US dollars. - Composites of changes in foreign trade volumes and prices are arithmetic averages of percent changes for individual countries weighted by the US dollar value of exports or imports as a share of total world or group exports or imports (in the preceding year). - Group composites are computed if 90 percent or more of the share of group weights is represented. - Data refer to calendar years except where countries use fiscal years; exceptional reporting periods are listed in Table F (not reproduced here). - For many countries conversion to updated statistical manuals will have only a small impact on major balances and aggregates; full concordance depends on national provision of revised data. ### Selected Country Notes and Special Issues - Afghanistan: Data for 2021 and 2022 are reported for selected indicators, with estimates for fiscal data. Estimates and projections for 2023–29 are omitted because of unusually high uncertainty owing to paused IMF engagement. Reported GDP growth rate for solar year 2021 is –20.7 percent (structural break due to change from calendar year to solar year). - Algeria: Total government expenditure and net lending/borrowing include net lending by the government, reflecting support to the pension system and other public sector entities. - Argentina: Official national CPI starts in December 2016; earlier periods use varying CPI series, and WEO does not report average CPI inflation for 2014–16 and end-of-period inflation for 2015–16. Labor market data discontinued starting Q4 2015; new series from Q2 2016. - Bangladesh: Data and forecasts presented on a fiscal year basis; country group aggregates use calendar year real GDP and PPP GDP. - Costa Rica: Central government definition was expanded as of January 1, 2021, to include 51 public entities; data back to 2019 are adjusted for comparability. - Dominican Republic: Fiscal series have specified coverage; public debt and related series are for the consolidated public sector; remaining fiscal series are for the central government. - Ecuador: Fiscal sector projections excluded from publication for 2024–29 because of ongoing program discussions. - Eritrea: Data and projections for 2020–29 are excluded because of constraints in data reporting. - India: Real GDP growth rates calculated in accordance with national accounts with base year 2011/12. - Iran: Nominal GDP in US dollars computed using the official exchange rate up to 2017; from 2018 onward the NIMA exchange rate is used to convert nominal rial GDP into US dollars. - Israel: Projections are subject to heightened uncertainty due to the conflict in Israel and Gaza and thus may undergo revisions. - Lebanon: Data for 2021–22 are IMF staff estimates and not provided by the national authorities. Estimates and projections for 2023–29 are omitted owing to an unusually high degree of uncertainty. - Sierra Leone: Currency redenomination on July 1, 2022; local currency data are expressed in the old leone for the April 2024 WEO. - Sri Lanka: Data and projections for 2023–29 are excluded from publication owing to ongoing discussions on sovereign debt restructuring. - Sudan: Projections reflect IMF staff’s analysis based on the assumption that the ongoing conflict will end by mid-2024. Data for 2011 exclude South Sudan after July 9; data for 2012 onward pertain to the current Sudan. - Syria: Data are excluded from 2011 onward because of the uncertain political situation. - Turkmenistan: Real GDP data are IMF staff estimates compiled in line with international methodologies (SNA); estimates and projections for the fiscal balance exclude receipts from domestic bond issuances and privatization operations, in line with GFSM 2014. - Ukraine: Revised national accounts data available beginning in 2000; data exclude Crimea and Sevastopol from 2010 onward. - Uruguay: Authorities began reporting national accounts data according to SNA 2008 with base year 2016; new series begin in 2016 and data prior to 2016 reflect IMF staff efforts to preserve previously reported data. Public pension system transfers in context of Law 19,590 of 2017 affected data for 2018–22 and amounted to 1.2 percent of GDP in 2018, 1.0 percent of GDP in 2019, 0.6 percent of GDP in 2020, and 0.3 percent of GDP in 2021. ### Coverage and Presentation Notes - The Statistical Appendix comprises eight sections: Assumptions, What’s New, Data and Conventions, Country Notes, Classification of Economies, General Features and Composition of Groups in the World Economic Outlook Classification, Key Data Documentation, and Statistical Tables. - Statistical Appendix A is included in the document; Statistical Appendix B is available online. - National statistical agencies are the ultimate providers of historical data and definitions; international organizations also contribute to harmonizing methodologies. - As more information becomes available, changes in data sources or instrument coverage can give rise to data revisions that are sometimes substantial. For clarification on deviations in sectoral or instrument coverage, consult the metadata for the online WEO database. *International Monetary Fund | April 2024 — CHAPTER 4 TRaDINg PLaCES: REaL SPILLOvERS FROM g20 EMERgINg MaRKETS — Statistical Appendix content (pages excerpt).* ### 0.1 percent of GDP in 2022, and 0 percent thereafter. ### text - 0.1 percent of GDP in 2022, and 0 percent thereafter. ### Fiscal data coverage and special cases - Uruguay - Coverage of fiscal data changed from consolidated public sector to nonfinancial public sector with the October 2019 WEO. - Nonfinancial public sector coverage includes the central government, local government, social security funds, nonfinancial public corporations, and Banco de Seguros del Estado. - The narrower fiscal perimeter excludes the central bank; assets and liabilities held by the nonfinancial public sector for which the counterpart is the central bank are not netted out in debt figures. - Capitalization bonds issued by the government to the central bank are now part of the nonfinancial public sector debt. - Reference: Staff Report for the 2018 Article IV Consultation, Country Report 19/64. - Venezuela - Projecting the economic outlook is made difficult by lack of discussions with the authorities (the most recent Article IV consultation took place in 2004), incomplete metadata for limited reported statistics, and difficulties reconciling reported indicators with economic developments. - Fiscal accounts include the budgetary central government; social security; FOGADE; and a reduced set of public enterprises, including Petróleos de Venezuela, S.A. - Following methodological upgrades to achieve a more robust nominal GDP, historical data and indicators expressed as a percentage of GDP have been revised from 2012 onward. - For most indicators, data for 2018–22 are IMF staff estimates. - The effects of hyperinflation and paucity of reported data mean staff-projected macroeconomic indicators should be interpreted with caution; broad uncertainty surrounds the projections. - Venezuela’s consumer prices are excluded from all WEO group composites. - West Bank and Gaza - Projections for 2024–29 are excluded from publication owing to the unusually high degree of uncertainty. - Zimbabwe - Authorities finished redenominating national accounts statistics following the introduction in 2019 of the Real Time Gross Settlement dollar, later renamed the Zimbabwe dollar. - The Zimbabwe dollar previously ceased circulating in 2009; during 2009–19 Zimbabwe operated under a multicurrency regime with the US dollar as the unit of account. ### Classification of economies in the WEO - The WEO divides the world into two major groups: advanced economies and emerging market and developing economies. - Advanced Economies: 41 economies listed (Table B). - Emerging Market and Developing Economies: 155 economies (comprise all those not classified as advanced economies). - Subgroups and analytical breakdowns - Major advanced economies subgroup: the seven largest by GDP (United States, Japan, Germany, France, Italy, the United Kingdom, and Canada). - Euro area members are distinguished as a subgroup; composite data cover current members for all years. - Regional breakdowns for emerging market and developing economies: emerging and developing Asia; emerging and developing Europe; Latin America and the Caribbean; Middle East and Central Asia (comprising Caucasus and Central Asia; and Middle East, North Africa, Afghanistan, and Pakistan); and sub-Saharan Africa. - Analytical criteria include source of export earnings (fuel vs. nonfuel; focus on nonfuel primary products: SITCs 0, 1, 2, 4, and 68) and financial/income criteria (net creditor vs. net debtor; heavily indebted poor countries (HIPCs); low-income developing countries (LIDCs); emerging market and middle-income economies (EMMIEs)). - Economies are categorized by export-earnings source if their main source exceeded 50 percent of total exports on average between 2018 and 2022. - Group definitions and thresholds - LIDCs: per capita income levels below a certain threshold (based on $2,700 in 2017 as measured by the World Bank’s Atlas method and updated following new information in early 2024), structural features consistent with limited development, and external financial linkages insufficiently close for them to be widely seen as emerging market economies. - EMMIEs: emerging market and developing economies not classified as LIDCs. - Notes on omissions - Some economies remain outside the classification (examples: Cuba and the Democratic People’s Republic of Korea) because they are not IMF members and thus are not monitored. ### Statistical notes, data documentation, and procedures - Country-specific data and special treatments are tabulated in the Statistical Appendix (Tables A–G and country notes). - Table A: Classification by WEO groups and shares in aggregate GDP, exports of goods and services, and population, 2023 (percent shares; number of economies by group and region). - Table F: Economies with Exceptional Reporting Periods (national accounts / government finance reporting periods listed). - Table G: Key Data Documentation (national accounts, CPI, government finance, balance of payments — historical data source, latest actual annual data, system of national accounts in use, use of chain-weighted methodology, subsectors coverage, accounting practice). - Specific documentation examples preserved verbatim in the source: - “As used here, the terms ‘country’ and ‘economy’ do not always refer to a territorial entity that is a state as understood by international law and practice.” - Table footnotes and country notes identify cases where data are incomplete or special treatments apply (e.g., Syria and West Bank and Gaza omitted from certain composites for insufficient data). ### Economic policy assumptions underpinning projections (summary of Box A1) - Fiscal policy assumptions - Short-term fiscal projections based on officially announced budgets, adjusted for differences between national authorities and IMF staff assessments; when no official budget exists, projections incorporate likely policy measures. - Medium-term fiscal projections are based on a judgment about the most likely policy path; where insufficient information exists, an unchanged structural primary balance is assumed unless indicated otherwise. - Country-specific fiscal assumption highlights (selection from source text, preserved wording and numeric references where present): - Austria: Projections based on the 2024 budget; NGEU fund and latest announcements incorporated. - Belgium: Based on the Belgian Stability Programme 2023–26 and the 2024 Budgetary Plan. - Brazil: Fiscal projections for 2024 reflect current policies in place. - Canada: Projections use the Government of Canada’s 2023 Fall Economic Statement baseline and provincial updates. - China: IMF staff fiscal projections incorporate the 2024 budget and estimates of off-budget financing. - India: Projections based on available information on authorities’ fiscal plans; starting with FY2020/21 data, expenditure includes off-budget component of food subsidies. - Russia: Fiscal rule suspended in March 2022; 2023–25 budget based on a modified rule with benchmark oil and gas revenues fixed in rubles at Rub 8 trillion; Ministry of Finance proposed reverting to earlier fiscal rule from 2024 with benchmark oil price at $60 a barrel. - Saudi Arabia: Baseline fiscal projections based primarily on 2024 budget and recent official announcements; export oil revenues based on WEO baseline oil price assumptions. - United States: Fiscal projections based on the February 2024 Congressional Budget Office baseline, adjusted for IMF staff assumptions; projections incorporate effects of the Fiscal Responsibility Act. - Monetary policy assumptions - Based on each economy’s established policy framework; generally nonaccommodative over the business cycle (rates increase when inflation is expected to rise above acceptable range; decrease when slack significant). - Country-specific monetary assumptions (selection from source text): - Brazil: Assumptions consistent with convergence of inflation within the tolerance band by the end of 2024. - Canada: Projections reflect gradual unwinding of monetary policy tightening; inflation returns to 2 percent by early 2025. - China: Overall monetary stance moderately accommodative in 2023 and expected to remain broadly accommodative in 2024. - Euro area: Monetary policy assumptions drawn from a suite of models (semi-structural, DSGE, Taylor rule), market expectations, and ECB communications. - India: Projections consistent with achieving Reserve Bank of India’s inflation target over medium term. - Russia: Monetary policy projections assume a tight monetary policy stance by the Central Bank of the Russian Federation. - Singapore: Broad money projected to grow in line with projected nominal GDP; staff projections include GST increase from 8 percent to 9 percent on January 1, 2024, and carbon tax increases (S$5 to S$25 in 2024–25, S$45 in 2026–27). - United States: IMF staff expects the Federal Open Market Committee to continue to adjust the federal funds target rate in line with the broader macroeconomic outlook. ### Key explicit numeric and data points appearing in the text excerpt - “0.1 percent of GDP in 2022, and 0 percent thereafter.” - IMF Country Report cited: “Country Report 19/64.” - Uruguay: fiscal coverage change date — “October 2019 WEO.” - Venezuela: most recent Article IV consultation date — “2004”; historical revisions from “2012 onward”; IMF staff estimates for “2018–22.” - Classification counts and thresholds: - Advanced economies listed as “41” (Table B). - Emerging market and developing economies listed as “155.” - LIDC per capita income threshold based on “$2,700 in 2017” (World Bank Atlas method), updated in early 2024. - Specific policy and projection references preserved verbatim where given (examples in Box A1 descriptions above). *Source: International Monetary Fund, World Economic Outlook — Statistical Appendix, April 2024 (text excerpt).* ### Annex 1.SF.1 ### Annex 1.SF.1 ### Global outlook and risks - Executive Directors broadly agreed with staff’s assessment of the global economic outlook, risks, and policy priorities. - Continued global economic resilience and containment of financial sector risks over the last two years were welcomed despite significant central bank interest rate hikes aimed at restoring price stability. - The global economy may be approaching a soft landing, but future growth is expected to be low by historical standards because of: - still‑high borrowing costs, - a withdrawal of fiscal support, - weak productivity growth, - continued geopolitical tensions. - Most Directors agreed that increasing geoeconomic fragmentation will weigh on medium‑term growth; a few Directors highlighted that trade diversification will bring benefits. - Directors regretted that, for many emerging market and developing economies, the subdued prospects for global growth imply a slower convergence toward higher living standards. - Risks to the outlook are now more balanced, but important downside risks remain, including: - supply disruptions and new price spikes from geopolitical tensions that could raise interest rate expectations and prompt renewed volatility and sharp downturns in asset prices, - more persistent‑than‑expected inflation triggering capital flow movements, a sharp tightening of global financial conditions, exchange rate volatility, and pressure on external and financial sectors, - the risk that the cooling effects of past monetary policy tightening could be yet to come. - Directors noted growing stresses in the commercial real estate sector and residential housing markets in some countries. - Upside risks include a faster‑than‑expected decline in inflation and growth and productivity gains from enhanced structural reforms. ### Monetary policy guidance - Directors called on central banks to ensure that inflation returns to target smoothly by avoiding easing policy prematurely. - The pace of monetary policy normalization should: - remain data dependent, - be tailored to country circumstances, - be clearly communicated. - Where inflation and inflation expectations are approaching target, Directors agreed central banks should gradually move to a more neutral policy stance to avoid inflation target undershoots. ### Fiscal policy guidance - Noting elevated fiscal deficits and debt levels in many countries and rising debt service costs, Directors called for a gradual medium‑term fiscal consolidation to: - ensure debt sustainability, - rebuild room for budgetary maneuver, - support priority investments, - finance targeted social spending to protect the most vulnerable. - The fiscal adjustment would also support the disinflation process. - The pace of consolidation should depend on each country’s conditions and be embedded in a credible medium‑term fiscal framework. - Directors noted that historical data indicate spending pressures could rise as a result of the record number of elections this year. - Many economies face important medium‑term spending pressures stemming from aging populations, climate change, and development needs. - Most Directors agreed countries should boost long‑term growth by implementing well‑designed, cost‑effective fiscal policies that: - promote innovation, - facilitate technology diffusion. - Directors emphasized these policies should avoid protectionist measures. ### Financial stability and regulation - Directors reiterated that continued accumulation of public and private debt in many economies constitute medium‑term financial vulnerabilities. - Regulatory authorities should use supervisory tools, including stress tests, to ensure banks and nonbank financial institutions are resilient to credit risk and strains in commercial and residential real estate. - Given potential new risks associated with rapid growth in private credit, Directors saw merit in a more proactive regulatory and supervisory approach, including enhancing reporting requirements. - Noting cyber incidents are a rising financial stability concern, Directors recommended better cyber‑related governance arrangements and legislations. - Directors emphasized the need for a full and timely implementation of Basel III. ### Structural reforms and multilateral cooperation - Targeted and carefully sequenced structural reforms are needed to raise medium‑term growth prospects; recommended reforms include: - reducing the misallocation of capital and labor, - increasing female labor participation, - enhancing education, - strengthening governance, - reducing excessive business regulation and restrictions on trade, - harnessing the potential of artificial intelligence, - facilitating the green transition and building climate resilience while managing energy security risks. - Many Directors expressed support for regular coverage of climate issues in the Fund’s flagship reports. - Directors emphasized reinvigorating multilateral cooperation to: - limit the costs and risks of climate change, - speed the green transition, - safeguard the open and rule‑based international trading system, - facilitate debt restructuring processes, - strengthen the resilience of the international monetary system. *The following remarks were made by the Chair at the conclusion of the Executive Board’s discussion of the Fiscal Monitor, Global Financial Stability Report, and World Economic Outlook on April 3, 2024.* --- _Source: https://www.imf.org/-/media/files/publications/weo/2024/april/english/text.pdf_