## World Economic Outlook: Growth Slowdown, Precarious Recovery — Preface and Selected Chapters (April 2019)

## Source details

**Canonical URL:** [World Economic Outlook: Growth Slowdown, Precarious Recovery — Preface and Selected Chapters (April 2019)](https://www.imf.org/-/media/files/publications/weo/2019/april/english/text.pdf)

## Other formats

- [Markdown version](/-/media/files/publications/weo/2019/april/english/text.pdf.md)
- [Structured JSON version](/-/media/files/publications/weo/2019/april/english/text.pdf.json)

---

### Global outlook and headline projections
- Global growth projections and path:
  - "global growth is set to moderate from 3.6 percent in 2018 to 3.3 percent in 2019, and then to return to 3.6 percent in 2020."
  - Global growth peaked "at close to 4 percent in 2017" and "softened to 3.6 percent in 2018."
  - Beyond 2020, growth will "stabilize at around 3½ percent" (driven mainly by China and India).
  - "The WEO projects a decline in growth in 2019 for 70 percent of the global economy."
- Key short-term assumptions:
  - Real effective exchange rates: "assumed to have remained constant at their average levels during January 14 to February 11, 2019" (with ERM II currencies constant in nominal terms relative to the euro).
  - Oil price assumptions: "The average price of oil is assumed to be $59.16 a barrel in 2019 and $59.02 a barrel in 2020 and will remain unchanged in real terms over the medium term."
  - LIBOR and short-term rates: "the six-month London interbank offered rate (LIBOR) on US dollar deposits will average 3.2 percent in 2019 and 3.8 percent in 2020"; "the three-month euro deposit rate will average –0.3 percent in 2019 and –0.2 in 2020"; "the six-month Japanese yen deposit rate will yield, on average, 0.0 percent in 2019 and 2020."
- Forecast revisions relative to Oct 2018 WEO:
  - "Growth for 2018 was revised down by 0.1 percentage point."
  - "Forecasts were marked down by 0.4 percentage point for 2019 and 0.1 percentage point for 2020 relative to the October 2018 WEO."

### Recent developments and drivers of the slowdown
- Contributing factors to the 2018–19 slowdown:
  - "Escalation of US–China trade tensions."
  - "Macroeconomic stress in Argentina and Turkey."
  - "Disruptions to the auto sector in Germany (new emission standards)."
  - "Tighter credit policies in China."
  - "Financial tightening alongside normalization of monetary policy in larger advanced economies."
- Policy responses supporting a pickup in H2 2019:
  - "The US Federal Reserve paused interest rate increases and signaled no increases for the rest of the year."
  - "The European Central Bank, the Bank of Japan, and the Bank of England shifted to a more accommodative stance."
  - "China ramped up fiscal and monetary stimulus."
- Financial/real indicators:
  - "Despite financial market improvements, measures of industrial production, investment, and global trade remained weak."
  - Industrial production slowed "particularly for capital goods"; global trade growth slowed sharply from late 2017.

### Risks and vulnerabilities (tilted to the downside)
- Key downside risks:
  - "Renewal or escalation of trade tensions, potentially disrupting global supply chains."
  - "Downside surprises to growth in China."
  - "Heightened uncertainties surrounding Brexit" (including no-deal risk).
  - "Rapid tightening of financial conditions triggered by a risk-off episode or a no-deal Brexit."
  - "Significant financial vulnerabilities associated with large private and public sector debt, including sovereign-bank doom loop risks (for example, in Italy)."
- Longer-term risks:
  - "Climate change and political discord in the context of rising inequality could lower global potential output."
  - IPCC note: "global warming could reach 1.5°C above preindustrial levels between 2030 and 2052" at current rates.
- Financial conditions snapshot:
  - "As of early March: financial conditions were slightly tighter than in October but, in most cases, still accommodative—especially in the United States where bond yields dropped."

### Policy priorities and recommendations
- General guidance:
  - "Avoid costly policy mistakes; policymakers should work cooperatively to reduce policy uncertainty and support investment."
  - "Monetary policy should remain data dependent, be well communicated, and ensure that inflation expectations remain anchored."
  - "Fiscal policy should manage trade-offs between supporting demand and ensuring public debt sustainability; the optimal mix is country-specific."
  - "Financial sector policies must address vulnerabilities proactively by deploying macroprudential tools."
  - "Greater multilateral cooperation is needed to resolve trade conflicts, address climate change and cybersecurity risks, and improve the effectiveness of international taxation."
- If major risks materialize:
  - "Policy may require synchronized, country-specific stimulus across economies, complemented by accommodative monetary policy."
- Advanced-economy specifics:
  - "Monetary policy should remain accommodative until inflation shows clear signs of rising toward targets."
  - "Fiscal policy should emphasize measures that boost potential output and raise inclusiveness while keeping public finances sustainable."
  - Potential output growth in advanced economies "estimated in the range of 0.5–1.5 percent for most advanced economies."
- Emerging market and developing economies:
  - "Anchor inflation expectations where inflation remains high or recent currency depreciations threaten pass-through to domestic prices."
  - "Ensure debt ratios remain sustainable; improve revenue mobilization and target subsidies; strengthen macroprudential frameworks."
- Low-income countries:
  - "Contain buildup of debt while protecting measures for the vulnerable and progress toward the Sustainable Development Goals."

### Chapter highlights — Chapter 1: Global Prospects and Policies
- Main themes:
  - "Recent Developments: Global Expansion Loses Steam."
  - "The Forecast" and "Risks: Skewed to the Downside."
  - "Policy Priorities: Enhance Resilience, Raise Medium-Term Growth Prospects."
- Notable scenario:
  - A no-deal Brexit box with two scenarios (A and B) and common assumptions; Scenario B shows larger disruptions including border delays and substantial tightening in UK spreads.
  - Scenario B estimated GDP declines from trade disruptions:
    - "UK GDP decline in first year: 1.4 percent; second year: 0.8 percent."
    - "EU GDP decline in first year: 0.2 percent; second year: 0.1 percent."
    - "Global GDP decrease over same period (Scenario A): 0.2 percent."
  - Long-term effects of no-deal (both scenarios): "United Kingdom potential output lower by almost 3 percent; European Union potential output lower by about 0.3 percent; World GDP down by 0.1 percent."

### Chapter highlights — Chapter 2: The Rise of Corporate Market Power and its Macroeconomic Effects
- Measurement and scope:
  - Firm-level measures from ~900,000 firms across 27 countries; markups computed following De Loecker and Warzynski (2012).
- Key empirical findings:
  - "The (firm-revenue-weighted) average markup increased by 6 percent during 2000–15."
  - Level change: "average markup shows an increase from about 1.28 in 2000 to 1.36 in 2015."
  - Rise concentrated in advanced economies: "about 7.7 percent throughout 2000–15 in advanced economies versus only 1.8 percent for the group of emerging market economies covered."
  - "The increase is essentially concentrated in nonmanufacturing industries."
  - Markup increases concentrated in the top 10 percent of the markup distribution: "top decile firms increased their (weighted) average markup by more than 30 percent; the remaining nine deciles report a (weighted) average increase of just 2 percent."
- Macroeconomic effects quantified (selected):
  - Investment channel: "a 10 percentage point increase in a firm’s markup is associated with a statistically significant 0.6 percentage point decrease in its physical capital investment rate."
  - Aggregate implication: "because of this investment channel, output would be about 1 percent higher today in the average advanced economy if markups had not increased since 2000" (ignoring enabling technological effects).
  - Labor share: a "10 percentage point" markup increase is associated with "a statistically significant 0.3 percentage point decrease in the labor share"; average sample rise in markups since 2000 is associated with about "0.2 percentage point decrease in the labor share" — "at least 10 percent of the trend decline in the labor share in the average advanced economy."
  - Natural rate: model suggests "the natural interest rate about 10 basis points lower" by 2015 due to markup trends; alternative statement: "10 basis point reduction in the annual natural interest rate by 2015."
- Policy implications:
  - Strengthen competition: "cutting domestic barriers to entry in nonmanufacturing industries; liberalizing trade and foreign direct investment; adjusting competition policy frameworks."
  - Corporate taxation: shift burden toward economic rent via "cash flow taxes (allowing investment to be expensed) or by providing an allowance for corporate equity."

### Chapter highlights — Chapter 3: The Price of Capital Goods: A Driver of Investment under Threat?
- Stylized facts:
  - "Relative price of machinery and equipment fell by about 60 percent in advanced economies and 40 percent in emerging market and developing economies" (since early 1990s, Penn World Table 9.0).
  - "Computing equipment prices fell by 90 percent since 1990"; "communications equipment prices fell by almost 60 percent."
- Commodity and trade drivers:
  - Declines driven by "faster productivity growth in capital-goods production and deepening trade integration."
  - Trade costs and productivity differences explain cross-country variance; tariffs and import-related costs matter.
- Projections and sensitivities:
  - Commodity-price assumptions (alternate figures in chapter): "Based on oil futures contracts, average oil prices are projected at $54.1 in 2019, rising to $55.2 in 2020" (section-specific); elsewhere baseline oil noted as "$59.16 in 2019 and $59.02 in 2020" — both figures preserved as in source (context-specific).
  - Metal prices: "expected to decline 6.0 percent year over year in 2019 and inch down a further 0.8 percent in 2020."
  - Food prices: "projected to decline 2.6 percent year over year in 2019 before increasing by 1.7 percent in 2020."
- Investment elasticity and simulations:
  - "A 1 percent decline in the price of investment relative to consumption leads to a roughly 0.8 percent increase in the ratio of real investment to real GDP in the medium term" (model result).
  - Empirical five-year regressions: estimated elasticities of real investment-to-GDP ratio to log relative price range from about –0.3 to –0.5 (Table 3.2 selected coefficients), e.g., Column (1) All: coefficient on Log Relative Price = –0.377***; Column (3) EMDEs = –0.491*** (standard errors and sample sizes preserved in source).
- Policy recommendations:
  - "Reduce trade costs and reinvigorate international trade"; lower capital goods tariffs, improve logistics and regulatory cooperation.
  - "Support continued technological progress and innovation in capital goods production" via R&D, education and infrastructure.

### Chapter highlights — Chapter 4: The Drivers of Bilateral Trade and the Spillovers from Tariffs
- Main findings on bilateral vs aggregate balances:
  - "Overall trade balances matter more than bilateral trade balances"; changes in aggregate balances tend to affect most bilateral balances.
  - "Macroeconomic factors play the dominant role" in changes in bilateral trade balances over 1995–2015; changes in bilateral tariffs played a smaller role.
- Gravity model and elasticities:
  - "A 1 percent increase in gross ad valorem tariffs reduces gross bilateral exports by about 3–6 percent" (range across specifications).
- Tariff spillovers and GVCs:
  - Upstream and downstream tariffs (tariffs along value chain) "matter for output and productivity generally much more than domestic protection tariffs."
  - Panel results: upstream and downstream tariffs have "statistically significant negative effects on value added, employment, labor productivity, and total factor productivity."
- Large-dispute simulations (US–China examples):
  - Hypothetical 25 percentage-point tariff increase on all US–China goods trade yields model ranges:
    - Short-term decline in US–China trade: "25–30 percent (GIMF Year 1)."
    - Long-term decline: "between 30 percent and 70 percent (model- and direction-dependent)."
    - Annual real GDP losses: "United States: –0.3 percent to –0.6 percent; China: –0.5 percent to –1.5 percent."
  - Third-country effects: "Mexico and Canada benefit most from diversion" but sectoral reallocation and job losses can be large in specific sectors (CFRT example: up to "about 1 percent" workforce shed in US agricultural and transportation equipment sectors; "about 5 percent" in China’s other manufacturing sector in CFRT).
- Policy conclusions:
  - Focus on macroeconomic determinants of aggregate current account balances; "multilateral reductions in tariffs and other nontariff barriers will benefit trade."

### Statistical Appendix, country tables, and assumptions
- Key statistical assumptions:
  - "Real effective exchange rates ... constant at their average levels during January 14 to February 11, 2019" (with ERM II exception).
  - "Estimates and projections are based on statistical information available through March 29, 2019."
  - Oil historical and assumed prices: "The average price of oil in US dollars a barrel was $68.33 in 2018; the assumed price, based on futures markets, is $59.16 in 2019 and $59.02 in 2020."
- Example regional projections (Annex Table 1.1.3, Western Hemisphere):
  - North America Real GDP: "2.7 (2018), 2.2 (2019), 1.9 (2020)"; United States Real GDP: "2.9 (2018), 2.3 (2019), 1.9 (2020)"; United States Unemployment: "3.9 (2018), 3.8 (2019), 3.7 (2020)."
  - South America aggregate Real GDP: "0.4 (2018), 1.1 (2019), 2.4 (2020)."
  - Venezuela projections (noting extreme values and data caveats): Real GDP: "–18.0 (2018), –25.0 (2019), –10.0 (2020)"; Consumer Prices: "929,789.5 (2018), 10,000,000 (2019), 10,000,000 (2020)"; Unemployment: "35.0 (2018), 44.3 (2019), 47.9 (2020)."
- Statistical conventions:
  - "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)."

### Selected notable tables and figures referenced
- Table 1.1: "Overview of the World Economic Outlook Projections" (contains World Output and Consumer Prices series and revisions).
  - Selected exact figures preserved in source: World Output row: "3.6 3.3 3.6 –0.2 0.0 –0.4 –0.1" (as in Table 1.1).
  - Consumer Prices (Advanced Economies): "2.0 1.6 2.1 –0.1 0.1 –0.3 0.1."
  - Consumer Prices (Emerging Market and Developing Economies): "4.8 4.9 4.7 –0.2 0.1 –0.3 0.1."
- Commodity indices and forecasts:
  - IMF Primary Commodity Price Index fell "by 6.9 percent between August 2018 and February 2019"; energy prices down "17.0 percent" in same period.
  - IMF annual base metal price index projection: "increase by 2.4 percent in 2019 and decrease by 2.2 percent per year in 2020."
  - Oil production and OPEC cuts: "US crude oil production averaged 10.9 million barrels a day (mbd) in 2018, an increase of 1.6 mbd"; OPEC/non-OPEC cuts "0.8 mbd and 0.4 mbd, respectively."
- Nowcasting/forecasting using commodity-price latent factors (Chapter 3 special feature):
  - First two principal components "explain about 20 percent of the variance in commodity price monthly changes."
  - GDP nowcast RMSE improvements: one-month information RMSE ratio "1.0, 0.90, 0.90, 0.90" across specifications (benchmark and specifications 1–3) as in Table 1.SF.3.
  - Industrial production forecasting: Specification 2 (two factors) improved forecast by "10 percent" relative to benchmark in some specifications.

### Selected scenario and policy simulation magnitudes (preserved)
- No-deal Brexit Scenario B (border disruption + tighter financial conditions):
  - UK first-year GDP decline: "1.4 percent"; second-year: "0.8 percent."
  - EU first-year GDP decline: "0.2 percent"; second-year: "0.1 percent."
  - Financial tightening in Scenario B: "UK sovereign spreads increase by 100 basis points and UK corporate spreads increase by 150 basis points"; temporary increases in corporate spreads: "European Union by 25 basis points; rest of the world by 15 basis points."
- US–China 25 percentage-point tariff simulation (selected model ranges):
  - US annual GDP losses between "–0.3 percent to –0.6 percent"; China losses "–0.5 percent to –1.5 percent."
  - US–China bilateral trade collapse short-term: "25–30 percent"; long term "between 30 percent and 70 percent" depending on model.

*Source: Preface, chapter excerpts, annex tables, and Statistical Appendix from World Economic Outlook: Growth Slowdown, Precarious Recovery (April 2019), International Monetary Fund.*

### Preface                                                                                                                 

### Preface

### Document scope and high-level structure
- World Economic Outlook: GROWTH SLOWDOWN, PRECARIOUS RECOVERY
- International Monetary Fund | April 2019
- Preface appears on page xii
- Foreword appears on page xiii
- Executive Summary appears on page xv

### Major chapters and primary themes (chapter title — starting page)
- Chapter 1. Global Prospects and Policies — 1
  - Recent Developments: Global Expansion Loses Steam — 1
  - The Forecast — 7
  - Risks: Skewed to the Downside — 19
  - Policy Priorities: Enhance Resilience, Raise Medium-Term Growth Prospects — 21
  - Scenario Box 1. A No-Deal Brexit — 28
  - Box 1.1. Labor Market Dynamics in Select Advanced Economies — 32
  - Box 1.2. Global Growth Forecast: Assumptions on Policies, Financial Conditions, and Commodity Prices — 34
  - Box 1.3. Worlds Apart? Within-Country Regional Disparities — 35
  - Special Feature: Commodity Market Developments and Forecasts — 37
  - References — 53
  - Online Annexes; Special Feature Online Annex

- Chapter 2. The Rise of Corporate Market Power and its Macroeconomic Effects — 55
  - Introduction — 55
  - The Rise of Corporate Market Power — 58
  - Macroeconomic Implications of Rising Market Power — 62
  - Summary and Policy Implications — 67
  - Box 2.1. The Comovement between Industry Concentration and Corporate Saving — 70
  - Box 2.2. Effects of Mergers and Acquisitions on Market Power — 72
  - References — 74
  - Online Annexes
    - Annex 2.1. Data Sources and Sample
    - Annex 2.2. Assessing Corporate Market Power: Methodologies and Further Stylized Facts
    - Annex 2.3. Assessing the Macroeconomic Implications of Rising Market Power: Methodological Details and Results

- Chapter 3. The Price of Capital Goods: A Driver of Investment under Threat? — 77
  - Introduction — 77
  - The Price of Capital Goods: Key Patterns — 80
  - The Relative Price of Capital Goods: A Simple Framework — 83
  - Drivers of Relative Investment Prices — 83
  - Macroeconomic Implications of Shocks to the Price of Capital Goods — 88
  - Summary and Policy Implications — 91
  - Box 3.1. The Price of Manufactured Low-Carbon Energy Technologies — 93
  - Box 3.2. Evidence from Big Data: Capital Goods Prices across Countries — 95
  - Box 3.3. On the Underlying Source of Changes in Capital Goods Prices: A Model-Based Analysis — 96
  - Box 3.4. Capital Goods Tariffs and Investment: Firm-Level Evidence from Colombia — 98
  - References — 100
  - Online Annexes
    - Annex 3.1. Data Sources and Country Groupings
    - Annex 3.2. Supplementary Stylized Facts
    - Annex 3.3. Using Trade Data to Uncover Differences in Capital Goods Prices across Countries
    - Annex 3.4. Drivers of Relative Investment Prices: Across Countries
    - Annex 3.5. Drivers of Relative Investment Prices: Over Time
    - Annex 3.6. Empirical Evidence on the Impact of Relative Investment Prices on Investment Rates at the Country Level
    - Annex 3.7. Empirical Evidence on the Impact of Relative Investment Prices on Investment Rates at the Sector Level

- Chapter 4. The Drivers of Bilateral Trade and the Spillovers from Tariffs — 103
  - Introduction — 103
  - Stylized Facts — 105
  - Determinants of Bilateral Trade Balances — 109
  - The Role of Macroeconomic Factors — 113
  - A Closer Look at Tariffs and Their Spillovers — 115
  - Conclusion — 119
  - Box 4.1. Gross versus Value-Added Trade — 120
  - Box 4.2. Bilateral and Aggregate Trade Balances — 122
  - Box 4.3. Understanding Trade Deficit Adjustments: Does Bilateral Trade Play a Special Role? — 123
  - Box 4.4. The Global Macro and Micro Effects of a US–China Trade Dispute: Insights from Three Models — 124
  - References — 128
  - Online Annexes
    - Annex 4.1. Gravity Model, Data, and Estimation
    - Annex 4.2. Derivation of Relation between Bilateral and Aggregate Trade Balances
    - Annex 4.3. Tariff Spillovers: Technical and Data Appendices

### Statistical Appendix and supporting materials
- Statistical Appendix — 131
  - Assumptions — 131
  - What’s New — 132
  - Data and Conventions — 132
  - Country Notes — 133
  - Classification of Countries — 133
  - General Features and Composition of Groups in the World Economic Outlook Classification — 134
  - Table A. Classification by World Economic Outlook Groups and Their Shares in Aggregate GDP, Exports of Goods and Services, and Population, 2018 — 135
  - Table B. Advanced Economies by Subgroup — 136
  - Table C. European Union — 136
  - Table D. Emerging Market and Developing Economies by Region and Main Source of Export Earnings — 137
  - Table E. Emerging Market and Developing Economies by Region, Net External Position, and Status as Heavily Indebted Poor Countries and Low-Income Developing Countries — 138
  - Table F. Economies with Exceptional Reporting Periods — 140
  - Table G. Key Data Documentation — 141
  - Box A1. Economic Policy Assumptions Underlying the Projections for Selected Economies — 151

### Tables, boxes, and annex tables
- Key listed tables and their pages include:
  - Table 1.1. Overview of the World Economic Outlook Projections — 8
  - Scenario Table 1. Trade Assumptions in the Baseline, Scenario A, and Scenario B — 28
  - Table 1.SF.1. Commodity Price Cycle Descriptive Statistics — 41
  - Table 1.SF.2. Global Industrial Production Nowcast — 44
  - Table 1.SF.3. Global GDP Nowcast — 44
  - Table 1.SF.4. Forecasting Global Industrial Production and GDP — 45
- Annex Tables covering regional macro indicators:
  - Annex Table 1.1.1. European Economies: Real GDP, Consumer Prices, Current Account Balance, and Unemployment — 46
  - Annex Table 1.1.2. Asian and Pacific Economies: Real GDP, Consumer Prices, Current Account Balance, and Unemployment — 47
  - Annex Table 1.1.3. Western Hemisphere Economies: Real GDP, Consumer Prices, Current Account Balance, and Unemployment — 48
  - Annex Table 1.1.4. Commonwealth of Independent States Economies: Real GDP, Consumer Prices, Current Account Balance, and Unemployment — 49
  - Annex Table 1.1.5. Middle East, North African Economies, Afghanistan, and Pakistan: Real GDP, Consumer Prices, Current Account Balance, and Unemployment — 50
  - Annex Table 1.1.6. Sub-Saharan African Economies: Real GDP, Consumer Prices, Current Account Balance, and Unemployment — 51

*Source: Preface and table of contents from the World Economic Outlook: Growth Slowdown, Precarious Recovery (April 2019).*

### Annex Table 1.1.7. Summary of World Real per Capita Output                                                              

### Annex Table 1.1.7. Summary of World Real per Capita Output

### Editor's note
- On June 18, 2019 in the PDF version of this report, the data for Myanmar was corrected subsequent to publication for Statistical Appendix Tables A4, A7, and A12 as well as in the online-only Statistical Appendix Table B9.

### Assumptions and conventions
- Real effective exchange rates are assumed to have remained constant at their average levels during January 14 to February 11, 2019, except for those for the currencies participating in the European exchange rate mechanism II (ERM II), which are assumed to have remained constant in nominal terms relative to the euro.
- It is assumed that established policies of national authorities will be maintained (for specific assumptions about fiscal and monetary policies for selected economies, see Box A1 in the Statistical Appendix).
- The average price of oil is assumed to be $59.16 a barrel in 2019 and $59.02 a barrel in 2020 and will remain unchanged in real terms over the medium term.
- The six-month London interbank offered rate (LIBOR) on US dollar deposits will average 3.2 percent in 2019 and

*Source: WORLD ECONOMIC OUTLOOK: GROWTH SLOWDOWN, PRECARIOUS RECOVERY (April 2019) — Annex Table 1.1.7.*

### 3.8 percent in 2020; that the three-month euro deposit rate will average –0.3 percent in 2019 and –0.2 in 2020;

### text - 3.8 percent in 2020; that the three-month euro deposit rate will average –0.3 percent in 2019 and –0.2 in 2020;

### Working hypotheses and short-term interest rate assumptions
- The three-month euro deposit rate will average –0.3 percent in 2019 and –0.2 in 2020.
- The six-month Japanese yen deposit rate will yield, on average, 0.0 percent in 2019 and 2020, respectively.
- These assumptions are described as working hypotheses rather than forecasts.
- The estimates and projections are based on statistical information available through March 29, 2019.

### Key global growth projections and recent trajectory
- Global growth peaked at close to 4 percent in 2017.
- Global growth softened to 3.6 percent in 2018.
- Global growth is projected to decline to 3.3 percent in 2019.
- Global growth is projected to return to 3.6 percent in 2020 (contingent on a rebound in Argentina and Turkey and improvements in other stressed economies).
- Beyond 2020, growth will stabilize at around 3½ percent, driven mainly by China and India.
- Growth in advanced economies will continue to slow gradually as US fiscal stimulus fades and growth tends toward modest long-term potential.
- Growth in emerging market and developing economies will stabilize at around 5 percent, with considerable variance between countries.
- The WEO projects a decline in growth in 2019 for 70 percent of the global economy.

### Recent developments affecting the outlook
- Contributing factors to the slowdown in 2018 included:
  - Escalation of US–China trade tensions.
  - Macroeconomic stress in Argentina and Turkey.
  - Disruptions to the auto sector in Germany (new emission standards).
  - Tighter credit policies in China.
  - Financial tightening alongside normalization of monetary policy in larger advanced economies.
- Policy responses supporting a pickup in the second half of 2019:
  - The US Federal Reserve paused interest rate increases and signaled no increases for the rest of the year.
  - The European Central Bank, the Bank of Japan, and the Bank of England shifted to a more accommodative stance.
  - China ramped up fiscal and monetary stimulus.
  - Prospects of a US–China trade agreement improved market sentiment.
- Despite financial market improvements, measures of industrial production, investment, and global trade remained weak.

### Risks and vulnerabilities
- Key downside risks include:
  - Renewal or escalation of trade tensions, potentially disrupting global supply chains.
  - Downside surprises to growth in China.
  - Heightened uncertainties surrounding Brexit.
  - Rapid tightening of financial conditions triggered by a risk-off episode or a no-deal Brexit.
  - Significant financial vulnerabilities associated with large private and public sector debt, including sovereign-bank doom loop risks (for example, in Italy).
- Limited conventional monetary and fiscal space in some countries could constrain policy responses if downside risks materialize.

### Policy guidance and priorities
- Avoid costly policy mistakes; policymakers should work cooperatively to reduce policy uncertainty and support investment.
- Fiscal policy should manage trade-offs between supporting demand and ensuring public debt sustainability; the optimal mix is country-specific.
- Financial sector policies must address vulnerabilities proactively by deploying macroprudential tools.
- Monetary policy should remain data dependent, be well communicated, and ensure that inflation expectations remain anchored.
- Low-income commodity exporters should diversify away from commodities given the subdued outlook for commodity prices.
- Across economies, actions are needed to boost potential output, improve inclusiveness, and strengthen resilience.
- Greater multilateral cooperation is needed to resolve trade conflicts, address climate change and cybersecurity risks, and improve the effectiveness of international taxation.
- If major risks materialize, policy may require synchronized, country-specific stimulus across economies, complemented by accommodative monetary policy; synchronization can strengthen signaling effects and mitigate import leakages.
- Adequate resources for multilateral institutions remain essential to retain an effective global safety net.

### Conventions, data notes, and what is new in this WEO
- “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).
- Data refer to calendar years except for a few countries that use fiscal years (see Table F in the Statistical Appendix).
- For some countries, figures for 2018 and earlier are based on estimates rather than actual outturns (see Table G in the Statistical Appendix).
- What is new in this publication:
  - FYR Macedonia is now called North Macedonia.
  - In February 2019, Zimbabwe adopted a new local currency unit, the RTGS dollar, which has become the official unit of account; current data are based on IMF staff estimates of price and exchange rate developments in US (and RTGS) dollars.

*Source: World Economic Outlook (WEO) text, IMF, data and projections based on information available through March 29, 2019.*

### 3.3 percent in 2019, before returning to 3.6 percent

### 3.3 percent in 2019, before returning to 3.6 percent

### Global Outlook and Projections
- Global growth is projected at 3.3 percent in 2019, before returning to 3.6 percent in 2020.
- Growth for 2018 was revised down by 0.1 percentage point relative to the October 2018 World Economic Outlook (WEO).
- Forecasts were marked down by 0.4 percentage point for 2019 and 0.1 percentage point for 2020 relative to the October 2018 WEO.
- The current forecast envisages global growth will level off in the first half of 2019 and firm up after that.
- The projected pickup in the second half of 2019 is predicated on:
  - an ongoing buildup of policy stimulus in China,
  - recent improvements in global financial market sentiment,
  - the waning of some temporary drags on growth in the euro area,
  - gradual stabilization of conditions in stressed emerging market economies, including Argentina and Turkey.
- Improved momentum for emerging market and developing economies is projected to continue into 2020, primarily reflecting developments in economies currently experiencing macroeconomic distress—a forecast subject to notable uncertainty.
- Activity in advanced economies is projected to continue to slow gradually as the impact of US fiscal stimulus fades and growth tends toward the modest potential for the group.
- Beyond 2020, global growth is set to plateau at about 3.6 percent over the medium term, sustained by the increase in the relative size of economies such as China and India.

### Growth Patterns by Country Group
- Advanced economy growth drag factors:
  - tepid labor productivity growth,
  - slowing expansion of the labor force amid population aging.
- Emerging market and developing economies:
  - projected to stabilize slightly below 5 percent, with variation by region and country.
  - baseline outlook for emerging Asia remains favorable; China’s growth projected to slow gradually toward sustainable levels.
  - structural bottlenecks, slower advanced economy growth, high debt, and tighter financial conditions weigh on prospects in other regions.
- Convergence concerns:
  - For some 41 emerging market and developing economies (close to 10 percent of global GDP in purchasing-power-parity terms and with total population close to 1 billion), per capita incomes are projected to fall further behind those in advanced economies over the next five years.

### Risks (Tilted to the Downside)
- Upside possibility:
  - global growth could surprise favorably if trade differences are resolved quickly, boosting business confidence and investor sentiment.
- Downside risks include:
  - further escalation of trade tensions and increased policy uncertainty,
  - sharp deterioration in market sentiment leading to portfolio reallocations away from risk assets, wider spreads over safe-haven securities, and tighter financial conditions—particularly for vulnerable economies,
  - a no-deal Brexit,
  - persistently weak economic data pointing to a protracted global slowdown,
  - prolonged fiscal uncertainty and elevated yields in Italy, especially if coupled with a deeper recession,
  - a rapid reassessment by markets of the US monetary policy stance tightening global financial conditions.
- Longer-term risks:
  - climate change and political discord in the context of rising inequality could lower global potential output, with severe implications for vulnerable countries.

### Policy Priorities and Recommendations
- Main priority: avoid policy missteps that could harm economic activity amid waning global growth momentum and limited policy space.
- National-level policies should:
  - ensure monetary policy keeps inflation on track toward the central bank’s target (or stabilizes there if close to target) and that inflation expectations remain anchored,
  - use fiscal policy to manage trade-offs between supporting demand and keeping public debt on a sustainable path,
  - calibrate the pace of fiscal consolidation where needed—particularly when monetary policy is constrained—to secure stability while avoiding harm to near-term growth and depletion of programs protecting the vulnerable.
- If slowdown becomes more severe and protracted:
  - macroeconomic policies should become more accommodative, particularly where output remains below potential and financial stability is not at risk.
- Cross-cutting imperatives:
  - take actions to boost potential output growth, improve inclusiveness, and strengthen resilience.
- Multilateral priority:
  - resolve trade disagreements cooperatively without raising distortionary barriers.

### Recent Developments: Global Expansion Loses Steam
- After a near two-year upswing, global expansion decelerated in the second half of 2018.
- Contributing factors:
  - increase in trade tensions and tariff hikes between the United States and China,
  - decline in business confidence,
  - tightening of financial conditions,
  - higher policy uncertainty,
  - country- and sector-specific factors reducing momentum.
- Growth specifics:
  - After peaking at close to 4 percent in 2017, global growth was 3.8 percent in the first half of 2018, but dropped to 3.2 percent in the second half of the year.

### Emerging Market and Developing Economies: Selected Developments
- China:
  - domestic regulatory tightening to rein in debt and constrain shadow financial intermediation contributed to slower domestic investment, especially in infrastructure,
  - spending on durable consumption goods softened; automobile sales declined in 2018 after expiration of incentive programs,
  - export orders diminished as US tariff actions began to take hold in the second half of the year,
  - China’s growth declined from 6.8 percent in the first half of 2018 to 6.0 percent in the second half of the year.
- Other emerging markets:
  - momentum moderated as worsening global financial market sentiment compounded country-specific factors,
  - Argentina and Turkey implemented needed policy tightening to reduce imbalances,
  - Mexico experienced weaker sentiment and rising sovereign spreads following policy reversals,
  - geopolitical tensions weighed on activity in the Middle East.

### Advanced Economies: Selected Developments
- Euro area slowdown drivers:
  - weakening consumer and business sentiment,
  - delays from introduction of new fuel emission standards for diesel-powered vehicles in Germany,
  - fiscal policy uncertainty, elevated sovereign spreads, and softening investment in Italy,
  - street protests disrupting retail sales in France,
  - concerns about a no-deal Brexit likely weighing on investment.
- Other advanced economies:
  - activity weakened in Japan largely due to natural disasters in Q3 2018,
  - United States momentum remained robust amid a tight labor market and strong consumption growth, though investment softened in H2 2018.

### Trade, Industrial Production, and Inflation
- Industrial production decelerated, particularly for capital goods; slowdown broad based across advanced economies except the United States.
- Global trade growth slowed sharply from its peak in late 2017; US imports from China subject to new US tariffs declined or stalled toward the end of the year after some front-loading.
- Commodity prices:
  - global energy prices declined by 17 percent between the reference periods for the October 2018 and current WEO as oil prices dropped from $81 a barrel in October to $61 in February,
  - prices of base metals increased by 7.6 percent since August owing to supply disruptions offsetting subdued demand.
- Inflation:
  - consumer price inflation remained muted across advanced economies given the drop in commodity prices; core inflation in many advanced economies is well below central bank targets, though in the United States and United Kingdom it is close to 2 percent,
  - among emerging market economies, core inflation remained below 2 percent in China; in some economies currency depreciations passed through to higher domestic prices.

### Financial Conditions
- Financial conditions tightened notably in late 2018, then rebounded in early 2019.
- Factors affecting sentiment:
  - slowing global growth, moderately less buoyant corporate earnings, market concerns about the pace of Federal Reserve policy tightening in late 2018,
  - prospects for a disorderly Brexit and macroeconomic stimulus and liquidity support in China influenced market movements,
  - a shift toward more accommodative monetary policy stances by major central banks (including a pause in US interest rate hikes) supported sentiment.
- As of early March:
  - financial conditions were slightly tighter than in October but, in most cases, still accommodative—especially in the United States where bond yields dropped as investors reassessed monetary policy normalization prospects.
- Central bank communications:
  - January communications by the US Federal Reserve suggested a patient and flexible approach; the March FOMC signaled a pause in interest rate hikes for the year,
  - the European Central Bank ended net asset purchases in December, announced a new round of targeted bank financing in March, and further postponed a rise in policy rates to at least the end of the year,
  - Bank of England and Bank of Japan adopted more cautious views on the outlook.

*Source: International Monetary Fund | April 2019*

### 4. Consumer Price Inflation Expectations

### 4. Consumer Price Inflation Expectations

### Overview
- Figures and charts in this section present measures of global inflation and consumer price inflation expectations using moving-average and year-over-year conventions:
  - "Figure 1.4. Global Inflation (Three-month moving average; annualized percent change, unless noted otherwise)"
  - "3. Core Consumer Price Inflation (Three-month moving average; year-over-year percent change)"
- Comparisons are drawn across country groups and selected economies: Advanced Economies (AEs) and Emerging Market and Developing Economies (EMDEs), and among the United States, United Kingdom, Euro area, and Japan.

### Metrics and Chart Conventions
- Global inflation: presented as three-month moving average; annualized percent change, unless noted otherwise.
- Core consumer price inflation: presented as three-month moving average; year-over-year percent change.
- Panels and labels reference:
  - "Core consumer price inflationConsumer price inflationUnited StatesUnited KingdomEuro areaJapanAEsEMDEs (right scale)"
- Real-time financial market context and related figures are dated through "March 22, 2019" where noted for financial market data.

### Key Statistics and Forecasts (preserved exactly as in source)
- Global growth and related consumer-price context:
  - "global growth is set to moderate from 3.6 percent in 2018 to 3.3 percent in 2019, and then to return to 3.6 percent in 2020."
  - "The forecast for 2019 is 0.4 percentage point lower than in the October 2018 WEO, while the forecast for 2020 is 0.1 percentage point lower (Table 1.1)."
- Consumer Prices (from Table 1.1; percent):
  - Advanced Economies: "2.0 1.6 2.1 –0.1 0.1 –0.3 0.1" (as presented in Table 1.1 under "Consumer Prices Advanced Economies")
  - Emerging Market and Developing Economies: "4.8 4.9 4.7 –0.2 0.1 –0.3 0.1" (as presented in Table 1.1 under "Consumer Prices Emerging Market and Developing Economies")
- Additional related projection context from Table 1.1 (selected exact figures relevant to inflation and the macro context):
  - World Output: "3.6 3.3 3.6 –0.2 0.0 –0.4 –0.1"
  - World Trade Volume (goods and services): "3.8 3.4 3.9 –0.6 –0.1 –0.6 –0.2"
  - Oil (commodity prices, US dollars): "29.4 –13.4 –0.2 0.7 0.2 –12.5 4.2"
  - Note on oil price assumption: "The average price of oil in US dollars a barrel was $68.33 in 2018; the assumed price, based on futures markets, is $59.16 in 2019 and $59.02 in 2020."
- Forecast assumptions and policy posture references:
  - "Fiscal policy is assumed to be expansionary across advanced economies in 2019 and expected to turn contractionary in 2020 as the US stimulus starts going into reverse."
  - "Across the emerging market and developing economy group, fiscal policy is assumed to be expansionary in 2019 (in part reflecting a projected fiscal stimulus in China to offset some of the negative effects of higher tariffs), before turning contractionary in 2020."
  - Trade policy assumption: "tariffs on $200 billion of US imports from China are assumed to stay at 10 percent"

### Interpretation Notes (from source text)
- The inflation measures are shown alongside broader macro and financial developments, including shifts in market expectations about US monetary policy, exchange rate movements, and emerging market financial conditions (financial market data are through "March 22, 2019").
- Charts in the section use groupings and scales that distinguish AEs and EMDEs (with EMDEs often shown on a right-hand scale where noted).

*Source: 4. Consumer Price Inflation Expectations, text - 4. Consumer Price Inflation Expectations*

### 1. Commodity and Oil Prices

### 1. Commodity and Oil Prices

### Commodity price assumptions
- Based on oil futures contracts, average oil prices are projected at $54.1 in 2019, rising to $55.2 in 2020.
- Metal prices are expected to decline 6.0 percent year over year in 2019 and inch down a further 0.8 percent in 2020.
- Food prices are projected to decline 2.6 percent year over year in 2019 before increasing by 1.7 percent in 2020.
- Sources: IMF, Primary Commodity Price System; and IMF staff estimates.
- Note: Data labels use International Organization for Standardization (ISO) country codes.

### Terms-of-trade windfall gains and losses
- Gains (losses) for 2019–20 are simple averages of annual incremental gains (losses) for 2019 and 2020.
- The windfall is an estimate of the change in disposable income arising from commodity price changes.
- The windfall gain in year t for a country exporting x US dollars of commodity A and importing m US dollars of commodity B in year t – 1 is defined as (Δp t A x t – 1 – Δp t B m t – 1) / Y t – 1, in which Δp t A and Δp t B are the percentage changes in the prices of A and B between year t – 1 and year t, and Y is GDP in year t – 1 in US dollars.
- See also Gruss (2014).

### Presentation and scope
- Figure referenced: Figure 1.12. Commodity Price Assumptions and Terms-of-Trade Windfall Gains and Losses (Percent of GDP, unless noted otherwise).
- Coverage includes commodity importers and exporters with data labels using ISO country codes.

*Source: IMF, Primary Commodity Price System; and IMF staff estimates.*

### 1. Advanced Economies

### 1. Advanced Economies

### Growth and Investment in Emerging Market and Developing Economies (context relevant to advanced economies)
- Over the forecast horizon, investment growth in emerging market and developing economies is projected to account for more than one-third of their GDP growth rate.
- Structural bottlenecks, subdued metal export prices, rising debt-service costs as financial conditions tighten globally, and difficult adjustment processes to diversify production structures away from resource extraction are expected to weigh on growth in many economies across the region.
- Medium-term outlook for the Middle East, North Africa, Afghanistan, and Pakistan (MENAP) region is shaped by the outlook for fuel prices, needed adjustment to correct macroeconomic imbalances in certain economies, and geopolitical tensions.
  - Growth in Saudi Arabia is expected to stabilize at about 2¼–2½ percent over the medium term.
  - In Pakistan, in the absence of further adjustment policies, growth is projected to remain subdued at about 2.5 percent.
- Convergence prospects:
  - Across sub-Saharan Africa and the MENAP region, 41 economies, accounting for close to 10 percent of global GDP in purchasing-power-parity terms and close to 1 billion in population, are projected to grow by less than advanced economies in per capita terms over the next five years.
  - Substantial heterogeneity exists within sub-Saharan Africa, where the majority of countries is projected to grow at rates well above the weighted average for the region.

### Inflation Outlook
- Advanced economies:
  - Inflation is expected to decline to 1.6 percent this year, from 2.0 percent in 2018.
  - With the US economy operating above potential this year and next, core inflation is expected to exceed the medium-term target of 2.0 percent, and decline to target thereafter.
  - In the euro area, core inflation is expected to gradually increase from 1.2 percent in 2018 to about 2 percent in 2022 as the economy is operating above potential.
  - Japan’s core inflation rate (excluding fresh food and energy) is projected to rise to 1.4 percent by the end of 2020 as the consumption tax rate is raised in October this year, softening back to about 1.3 percent in the medium term.
- Emerging market and developing economies (excluding Venezuela):
  - Inflation is expected to firm to 4.9 percent this year from 4.8 percent in 2018, reflecting developments in a few economies (temporary VAT increase in Russia; gradual pickup in India; elevated inflation expectations in Argentina during transition to a new monetary and exchange rate framework).
  - As these temporary effects fade and growth stabilizes across the group, inflation is set to moderate to about 4 percent over the medium term.

### External Sector Outlook

Trade Growth
- Global trade growth slowed considerably in 2018, reflecting payback from very high growth in late 2017, impact of increased trade tensions on spending on capital goods, and a general slowdown in global activity.
- Forecast for 2019 is for some further slowdown, followed by some recovery in 2020.
- In subsequent years, trade growth is projected to continue at broadly the same pace as in 2018 as investment demand gradually recovers in emerging market and developing economies, offsetting the slowdown in capital spending in advanced economies projected for 2020 and beyond.

Current Account Positions
- Global current account deficits and surpluses are estimated to have widened marginally in 2018 compared with the previous year; higher oil prices are the main driver.
  - Higher oil prices are estimated to have boosted the current account balance of oil exporters by about 3½ percent of their GDP.
- Major country/regional balances in 2018:
  - China current account surplus declined to 0.4 percent of GDP.
  - US current account deficit was unchanged at 2.3 percent of GDP.
  - Euro area surplus declined marginally to 3.0 percent of GDP.
- Forecasts for 2019 and beyond indicate a gradual reduction in global current account deficits and surpluses, particularly after 2020.
  - Surplus of oil exporters will fall as average oil prices are projected to drop from their 2018 level.
  - Current account surpluses in the euro area, Japan, and other advanced Asian economies are projected to decline gradually.
  - US current account balance is projected to widen in 2019–20—driven by expansionary fiscal policy—and to narrow again thereafter.
- Imbalances relative to country-specific norms:
  - Excess current account balances in 2018 are estimated to have declined, supported in many cases by real exchange rate movements.
  - The change in the current account balance during 2018 is estimated to have offset, on average, about one-fifth of the 2017 current account gap; the change between 2017 and 2024 would offset less than half of the 2017 gap.

International Investment Positions
- Changes in international investment positions reflect net financial flows and valuation changes from exchange rates and asset prices; WEO projections assume broadly stable real effective exchange rates and limited variation in asset prices.
- Projected dynamics:
  - Creditor and debtor positions as a share of world GDP are projected to widen slightly this year, and then to broadly stabilize as a share of world GDP over the forecast horizon.
  - Growing creditor positions of a group of European advanced economies (result of large projected current account surpluses) are offset by some reduction in the creditor position of China and oil exporters.
  - Debtor side: United States debtor position increases initially and then stabilizes with forecast reduction in its current account deficit as fiscal stimulus is withdrawn; euro area debtor countries’ positions improve significantly.
- By 2024 projections:
  - Net creditor position of advanced European economies projected to be above 80 percent of GDP.
  - Japan’s net creditor position projected to exceed 65 percent of GDP.
  - China’s net creditor position projected to decline to below 10 percent of GDP.
  - United States debtor position projected to approach 50 percent of GDP, some 9 percentage points above the 2017 estimate.
  - Net international investment position of a group of euro area debtor countries (including Italy and Spain) expected to improve by more than 25 percentage points of their collective GDP.
  - By 2024, net foreign liabilities, at about 32 percent of their GDP, would be half what they were a decade earlier.

### Implications of Imbalances and Policy Recommendations
- Risks from sustained excess external imbalances and policy actions that widen them:
  - Fiscal easing in the United States is projected to increase the US current account deficit, which could aggravate trade tensions and result in a faster tightening of global financing conditions, negatively affecting emerging market economies with weak external positions.
  - Over the medium term, widening debtor positions in key economies could constrain global growth and possibly result in sharp and disruptive currency and asset price adjustments.
- Policy priorities cited:
  - The US economy—which is already operating beyond full employment—should implement a medium-term plan to reverse the rising ratio of public debt, accompanied by fiscal measures to gradually boost domestic capacity. This would help ensure more sustainable growth dynamics and contain external imbalances.
  - Stronger reliance on demand growth in some creditor countries, especially those, such as Germany, with the policy space to support it, would help facilitate global rebalancing and reduce pressures from excess external imbalances.

*Source: IMF staff estimates and World Economic Outlook (April 2019) chapter excerpt.*

### CHAPTER 1

### CHAPTER 1

### Risks: Skewed to the Downside
- Global growth is expected to stabilize in the first half of 2019 and recover gradually thereafter, but the balance of risks remains skewed to the downside.
- Key sources of downside risk:
  - Trade tensions:
    - Ongoing trade tensions threaten global trade, investment, and output.
    - Noted developments: signing of the US-Mexico-Canada Agreement on November 30, 2018; extension past March 1, 2019, of the truce between the United States and China on tariff increases; announced reduction in Chinese tariffs on US car imports.
    - Risks remain from unresolved US–China negotiations, domestic ratification processes for US-Mexico-Canada Agreement, and a US proposal to raise tariffs on all imported cars and car parts.
    - Potential effects of increased tariffs: higher costs of imported intermediate and capital goods; higher final goods prices; reduced business investment; disrupted supply chains; slower productivity growth; depressed corporate profitability; deteriorated financial market sentiment.
  - Downside risks in systemic economies:
    - Europe:
      - A protracted period of elevated yields in Italy could stress Italian banks, weigh on economic activity, and worsen debt dynamics.
      - Rising possibility of a no-deal Brexit and adverse European Parliamentary election outcomes could delay or reverse progress on strengthening euro area architecture.
      - A no-deal Brexit that severely disrupts supply chains and raises trade costs could have large and long-lasting negative impacts on the United Kingdom and the European Union.
    - United States:
      - Market-implied expected policy rates remain below the Federal Open Market Committee’s projections, implying possible market reassessment if US data remain strong.
      - Reassessment could cause higher US interest rates, renewed dollar appreciation, and tighter financial conditions for emerging market and developing economies with balance sheet vulnerabilities (elevated currency and maturity mismatches).
      - April 2019 GFSR notes the US credit cycle is at an advanced stage: rising share of lower-rated issuers in the corporate bond market and growing volume of covenant-lite loans to highly indebted companies.
      - If US growth weakens, financial fragilities could amplify the slowdown via debt-service difficulties, credit rating downgrades, and rising rollover risks.
    - China:
      - Authorities limited financial regulatory tightening, injected liquidity via cuts in bank reserve requirements, and reduced the personal income tax and value-added tax for small and medium enterprises in response to the 2018 slowdown.
      - If trade tensions persist, activity may fall short of expectations.
      - Excessive stimulus (loosening credit standards, resurgence of shadow banking, off-budget infrastructure spending) would heighten financial vulnerabilities, reduce future policy space, and raise downside risks to medium-term growth.
  - Other financial vulnerabilities:
    - Cyberattacks on financial infrastructure could severely disrupt cross-border payment systems and flows of goods and services.
    - Reversals of postcrisis regulatory reform or continued accommodative financial conditions could foster additional financial vulnerabilities, especially if intermediaries search for returns amid slower global growth.
  - Political uncertainty:
    - Policy uncertainty from new administrations or elections, geopolitical conflict in the Middle East, and tensions in east Asia add downside risk.
    - A sequence of such events, combined with trade tensions and tighter global financial conditions, could have outsized effects on sentiment and broader reverberations.
  - Medium-term risks:
    - Climate change and declining trust in establishment institutions and political parties pose slower-moving risks with serious medium- and long-term implications.
    - IPCC (October 2018) reported that, at current rates, global warming could reach 1.5°C above preindustrial levels between 2030 and 2052, bringing extremes of temperature, precipitation, and drought, with devastating humanitarian effects and severe, persistent output losses.

### Fan Chart and Growth-at-Risk Analysis
- Fan chart analysis (based on equity and commodity market data and dispersion of private forecasters’ projections) shows a downward shift in the balance of risks relative to the April 2018 WEO.
- The worsening profile largely reflects anticipated drag from the risk of oil prices rebounding sharply from their recent rapid drop.
- Growth-at-risk analysis (April 2019 GFSR) suggests slightly higher near-term downside risks to global financial stability compared with October 2018, and continued elevated risks to medium-term growth.

### Policy Priorities: Enhance Resilience, Raise Medium-Term Growth Prospects
- Main priorities:
  - Avoid policy missteps that could harm activity.
  - Guard against further deceleration where output may fall below potential and ensure a soft landing where policy support needs withdrawal.
- Macroeconomic policy guidance:
  - Monetary policy: aim to keep inflation on track toward central bank targets and keep inflation expectations anchored.
  - Fiscal policy: manage trade-offs between supporting demand and ensuring public debt remains on a sustainable path; calibrate consolidation pace to secure stability without suppressing near-term growth or harming programs that protect the vulnerable.
  - Financial sector policies: secure balance sheet strength and address vulnerabilities proactively with macroprudential tools.
    - Examples: countercyclical capital buffers; targeted sectoral capital buffers (or higher risk weights and provisions on such exposures); borrower-based tools to mitigate high debt vulnerabilities.
  - If the slowdown becomes more severe and protracted:
    - Policy stance should become more accommodative where output is or could fall below potential and where policy space exists.
    - If fiscal consolidation is underway and monetary policy is constrained, consolidation pace should slow to support near-term demand.
    - Clear communication and cooperative efforts (e.g., on US–China trade dispute and Brexit) become more important where worsening outlook and market sentiment reinforce each other.
- Medium-term priorities:
  - World baseline projects broadly stable growth at 3.6 percent beyond 2020, relying partly on shifting weights toward higher-growth regions.
  - Advanced economies should focus on boosting potential output and inclusiveness; measures include raising labor force participation and productivity via:
    - Public investment (with incentives to raise private spending as needed) in infrastructure.
    - Lifelong learning and workforce skills.
    - Research and development.
    - Competition policy frameworks to facilitate new firm entry and curb incumbents’ market power.
  - Emerging market and developing economies should strengthen revenue bases to finance social and infrastructure spending; this supports sustained poverty reduction, increased inclusiveness, and debt sustainability.
  - Ensure gains reach all segments via adequate social spending on education, health, and safety nets.

### Advanced Economies — Specific Policy Guidance
- Current environment:
  - Consumer price inflation generally remains below target; wage pressures are relatively subdued (picking up in a few cases).
- Policy recommendations:
  - Monetary policy should remain accommodative until inflation shows clear signs of rising toward targets.
  - Fiscal policy should emphasize measures that boost potential output and raise inclusiveness while keeping public finances sustainable.
  - Where public debt is high, pursue gradual fiscal consolidation that avoids sharp growth drags and secures adequate social insurance.
  - If a substantially deeper and more protracted slowdown materializes, both monetary and fiscal policy should become more accommodative.
  - Safeguard financial systems by:
    - Raising bank capital and liquidity buffers.
    - Enhancing macroprudential oversight of nonbank financial institutions.
    - Developing macroprudential tools where needed.
    - Avoiding rollback of postcrisis regulatory reforms.
- Potential output:
  - Potential output growth rates are estimated in the range of 0.5–1.5 percent for most advanced economies.
- United States-specific guidance:
  - With output above potential, the Federal Reserve’s patient approach to normalization is appropriate given baseline uncertainty and muted inflation.
  - Policy interest rate path should depend on incoming data, outlook, and risks.
  - Under the WEO baseline, labor markets are expected to tighten further and wage growth to pick up, likely warranting a further rate hike in the second half of the year.
  - Risks of policy mis-timing:
    - Rapid tightening could weaken inflation expectations and activity.
    - Delayed tightening could contribute to financial vulnerabilities and a sharper downturn later.
  - The 2017 tax overhaul and subsequent increases in spending have widened the fiscal deficit and added to an already...

*Source: CHAPTER 1, text - CHAPTER 1 (International Monetary Fund | April 2019).*

### CHAPTER 1

### CHAPTER 1

### Advanced economies: overview and policy guidance
- Fiscal policy should focus on raising the revenue-to-GDP ratio, with greater reliance on indirect taxes to counteract the anticipated rise in aging-related spending.
- Preserve the current risk-based approach to financial regulation, supervision, and resolution; strengthen it for nonbank financial institutions to counteract vulnerabilities from weaker corporate credit underwriting standards, rising corporate leverage, and emerging cybersecurity threats.
- Improve medium-term growth prospects by incentivizing greater labor force participation and enhancing workforce skills.
- Monetary policy should be data-dependent and cautious where uncertainty is high (for example, the United Kingdom and euro area).
- Where inflation is below target or wage growth sluggish (e.g., euro area), monetary policy should remain accommodative; forward guidance on reinvestment of maturing securities is welcomed.
- If a severe downside scenario materializes in the euro area, available monetary policy tools could be complemented with fiscal easing by countries with appropriate fiscal space and financing conditions; a synchronized fiscal response, appropriately differentiated across member countries, can strengthen area-wide impact.
- Completing the banking union and continuing cleanup of bank balance sheets remain vital to strengthen credit intermediation in some economies.

### Advanced economies: country-specific priorities
- United States
  - Policy concern: unsustainable US public debt profile.
  - Recommendation: raise the revenue-to-GDP ratio; rely more on indirect taxes to offset aging-related spending.
- United Kingdom
  - Context: historically low unemployment and a recent pickup in wage growth.
  - Recommendation: cautious, data-dependent monetary response given Brexit uncertainty; adjust envisaged fiscal consolidation if growth slows materially.
  - Structural reforms: improve infrastructure quality; boost basic skills of high school graduates; labor market policies to ensure redeployment of workers to expanding sectors post-Brexit.
- Euro area
  - Observation: core inflation remains well below target and wage growth relatively sluggish despite tightening labor markets.
  - Fiscal guidance:
    - In some countries (France, Italy, Spain) rebuild buffers gradually to avoid reigniting adverse sovereign-bank feedback and to secure stability.
    - In Germany, available fiscal space can be used to increase public investment in physical and human capital or reduce the labor tax wedge.
  - Structural reform priorities by country:
    - France: reduce corporate administrative burdens, promote innovation, strengthen competition in services, improve labor market flexibility.
    - Italy: decentralize wage bargaining to align wages and labor productivity.
    - Spain: reduce labor market duality to support job creation and incentivize private investment.
- Japan
  - Monetary policy: sustained accommodation necessary to lift inflation expectations and progress toward the central bank’s target.
  - Fiscal policy: ensure long-term fiscal sustainability while protecting growth; coupling the planned October increase in the consumption tax rate with fiscal measures to support near-term activity is welcome.
  - Debt and social policy: further gradual and steady increases in the consumption tax rate and reforms of the social security framework are needed for a sustainable debt trajectory.
  - Structural priorities: lift productivity growth and wage inflation by reducing labor market duality; raise female labor force supply and encourage more use of foreign labor to counteract aging-induced decline in labor force growth.

### Emerging market and developing economies — overarching policy priorities
- Monetary policy
  - Anchor inflation expectations where inflation remains high or recent currency depreciations threaten pass-through to domestic prices.
  - Where expectations are well anchored, monetary policy can support domestic activity as needed.
- Fiscal policy
  - Ensure debt ratios remain sustainable to contain borrowing costs and create space to combat downturns.
  - Improve targeting of subsidies, rationalize recurrent expenditures, and mobilize revenue to preserve capital outlays and social spending.
- Macroprudential and financial sector policies
  - Strengthen frameworks to deal with high private debt burdens, rein in excess credit growth, and contain balance sheet currency and maturity mismatches.
- Exchange rate flexibility can complement policies by buffering shocks and preventing persistent relative price misalignments.
- Reforms for sustainable, inclusive growth remain essential given relatively subdued medium-term prospects for per capita growth in many economies in this group.

### Emerging market and developing economies: country-level guidance
- China
  - Progress: reliance on credit has declined somewhat after regulatory efforts to rein in shadow banking.
  - Policy focus: continue deleveraging and rebalance growth away from credit-fueled investment toward private consumption.
  - Specific actions: scale back implicit guarantees; early recognition and disposal of distressed assets; foster market-based credit allocation.
  - Social and tax policy: build on private consumption share of GDP, up close to 40 percent in 2017 from 35 percent in 2012, by instituting a more progressive tax code; increase spending on health, education, and social transfers; reduce barriers to labor mobility.
  - Structural reforms: reduce footprint of state-owned enterprises; reduce barriers to entry in sectors such as telecommunications and banking.
  - Near-term: some centrally financed on-budget fiscal expansion in 2019 may be appropriate, avoiding large-scale infrastructure stimulus and emphasizing targeted transfers to low-income households.
- India
  - Near-term: continued fiscal consolidation needed to bring down elevated public debt.
  - Policy measures: strengthen goods and services tax compliance; further reduce subsidies; accelerate resolution of nonperforming assets; enhance governance of public sector banks.
  - Structural reforms: reform hiring and dismissal regulations to incentivize job creation; advance land reform to facilitate infrastructure development.
- Argentina
  - Outlook: projections for growth have been revised upward; higher nominal wages and rising inflation expectations expected to generate more persistent inflationary pressures in 2019 than projected in the October 2018 WEO.
  - Priorities: continue implementation of stabilization plan under IMF-supported program to shore up investor confidence.
  - Fiscal targets: meet the primary fiscal balance target of zero in 2019 and 1 percent of GDP in 2020 to bring down financing needs and avoid reigniting liquidity pressures.
  - Monetary policy: continue achievement of monetary targets to re-anchor inflation expectations and rebuild central bank credibility.
  - Structural: resume structural reform agenda to lift medium-term growth prospects.
- Brazil
  - Priority: contain rising public debt while ensuring needed social spending remains intact.
  - Fiscal framework: the spending cap introduced in 2016 envisages a 0.5 percent of GDP a year improvement in the primary fiscal balance.
  - Recommendation: more up-front adjustment is needed—cuts to public wage bill and pension reforms—while protecting vital social programs.
  - Monetary policy: with inflation close to target, monetary policy can stay accommodative to support aggregate demand as needed.
  - Structural: improve infrastructure and efficiency of financial intermediation to lift productivity and medium-term growth.
- Mexico
  - Context: sovereign spreads have widened significantly since October.
  - Recommendation: avoid delaying needed structural reforms; stick with medium-term fiscal consolidation (and possibly aim for a larger reduction in the deficit) to stabilize public debt and lift confidence.
  - Monetary policy: provided inflation remains subdued and expectations well anchored, monetary policy can stay accommodative with scope to cut rates if needed.
- Turkey
  - Framework: the New Economic Program provides a framework to deal with complex issues.
  - Recommendation: implement a comprehensive and credible policy mix to secure macroeconomic stability.
  - Fiscal consolidation: pace should be calibrated given the subdued outlook.
  - Monetary policy: limited scope to support activity in context of high inflation and elevated inflation expectations.
  - Structural measures: rationalize spending channeled through public-private partnerships; increase transparency; strengthen financial balance sheets; address nonfinancial corporate sector stress and debt vulnerabilities.
- Russia
  - Recent policy: revision of the fiscal rule delivered a procyclical positive fiscal impulse and could weaken policy credibility.
  - Recommendation: further fiscal consolidation over the medium term to ensure sustainability.
  - Monetary policy: policy rate has been raised above the neutral rate following higher inflation pressure in the second half of 2018; if inflation does not rise, there is room to provide monetary support should activity weaken.
  - Structural: enhance bank efficiency, improve property rights and governance, reform labor markets, and invest in infrastructure to boost private investment and productivity.
- South Africa
  - Fiscal policy: gradual fiscal consolidation needed to stabilize public debt.
  - Recommendations: prioritize public wage savings to preserve social outlays and fund productive investment; make transfers to public entities contingent on downsizing and eliminating wasteful spending.
  - Revenue measures: expand tax base, strengthen tax administration, and implement anti-tax-avoidance provisions to reduce profit shifting.
  - Structural reforms: product and labor market reforms to expand private investment, job creation, and productivity growth.

### Low-income developing countries
- Shared priorities with emerging market group: raise resilience to volatile external conditions; strengthen monetary and macroprudential frameworks while preserving exchange rate flexibility.
- Risk: public debt stocks have increased rapidly during a period of low interest rates; as financial conditions tighten, rollover risks may increase and sovereign spreads may rise.
- Fiscal policy: contain buildup of debt while protecting measures for the vulnerable and progress toward the Sustainable Development Goals.
- Revenue and spending reforms: broaden the revenue base; strengthen tax administration; eliminate wasteful subsidies; prioritize infrastructure, health, education, and poverty reduction.
- Commodity exporters: face additional pressure from subdued commodity price outlook; reorient spending toward infrastructure and social outlays; boost domestic revenue mobilization.
- Diversification priorities: sound macroeconomic management; broaden labor force participation by improving education quality and worker skills; reduce infrastructure shortfalls; boost financial development and inclusion; incentivize firm entry and private investment via stronger property rights, contract enforcement, and reduced barriers to trade.
- Climate and disasters: invest in climate-smart infrastructure, incorporate appropriate technologies and zoning regulations, and deploy well-targeted social safety nets to lower fallout from climate change and natural disasters.

### Multilateral policies
- Trade
  - Cross-border integration through trade openness has been a critical source of productivity growth, knowledge diffusion, and welfare gains.
  - Policy recommendations:
    - Cooperate to address dissatisfaction with the rule-based trading system, reduce trade costs, and resolve disagreements without raising tariff and non-tariff barriers.
    - Unwind trade-restrictive measures implemented so far and modernize WTO rules to address services, e-commerce, subsidies, and technology transfer.
    - Ensure existing rules are applied and enforced, including resolving the impasse over the WTO’s Appellate Body.
    - Well-designed regional arrangements (for example, Comprehensive and Progressive Agreement for Trans-Pacific Partnership and EU-Japan Economic Partnership Agreement) can help.
    - Revisit the idea that all countries need to participate in all negotiations to allow willing countries to move faster while keeping agreements inside the WTO and open to all members.
- Global financial stability
  - Global cooperation is needed to safeguard postcrisis financial system gains and resist pressures to roll back reforms.
  - Implement the reform agenda fully, including:
    - implementing the leverage ratio and net stable funding ratio;
    - devising effective resolution frameworks and enhancing cross-border supervisory intensity for globally important financial institutions;
    - bolstering macroprudential tools and policymaking capabilities;
    - mitigating systemic risk from nonbank financial institutions by vigilance on the regulatory perimeter and filling data gaps.
  - Coordinated action needed to confront emerging risks from growing importance of central counterparties and potential cybersecurity breaches, and to combat cross-border money laundering and terrorism financing.
  - Maintain correspondent banking relationships vital to low-income countries’ access to international payment systems.
  - An adequately financed global safety net can protect economies with robust fundamentals from cross-border contagion when downside global risks are elevated.

*International Monetary Fund | April 2019*

### CHAPTER 1

### CHAPTER 1

### Taxation and Multilateral Cooperation
- With the rise of multinational enterprises, international tax competition has made it increasingly difficult for governments to collect revenues needed to finance their budgets.
- Multilateral cooperation is needed to reinforce existing efforts aimed at tackling tax evasion and avoidance and mitigation of tax competition, such as through the Organisation for Economic Co-operation and Development–Group of Twenty Base Erosion and Profit Shifting initiative (see Box 1.3 of the April 2019 Fiscal Monitor).

### Longer-Term Global Challenges
- Climate change
  - Curbing greenhouse gas emissions and containing the associated consequences of rising global temperatures and devastating climate events are a global imperative (see Chapter 3 of the October 2017 WEO and IMF 2019 for fiscal policy options for implementing climate change mitigation and adaptation strategies).
  - Climate-related events add to migrant flows and compound refugee flight from conflict areas, often to countries already under severe strain.
- International migration
  - Migration will become increasingly important as many advanced economies confront aging populations.
  - International cooperation could streamline migrant integration, maximize labor supply and productivity benefits to destination countries, and support remittance flows that lessen burdens on source countries.
- Corruption
  - A truly global effort is needed to curb corruption, which is undermining faith in government and institutions in many countries (see the April 2019 Fiscal Monitor).

### A No-Deal Brexit: Scenarios and Common Assumptions
- Model: IMF’s Global Integrated Monetary and Fiscal model; explores UK withdrawal from the EU without a free trade deal in Q2 2019.
- Two scenarios (compared with the April 2019 WEO baseline, which assumes a broad free trade agreement and gradual transition):
  - Scenario A: assumes no border disruptions and a relatively small increase in UK sovereign and corporate spreads.
  - Scenario B: incorporates significant border disruptions that increase import costs for UK firms and households and a more severe tightening in financial conditions.
- Common assumptions
  - Temporary measures already in place or announced to lower short-term impact, including temporary exemption of a large share of UK imports from tariffs and temporary recognition regimes for some financial services.
  - Trade with the European Union
    - Under no-deal, UK exports to the EU revert to WTO MFN rules, with tariffs increasing by mid-2019.
    - Imports from the EU not subject to the temporary tariff regime revert to MFN in mid-2019; those subject to the regime revert in mid-2020.
    - Overall, the reduction in nontariff barriers from UK EU membership—about 20 percent in tariff-equivalent terms—is eventually reversed.
  - Trade with countries outside the EU
    - The United Kingdom loses most third-country free trade agreements currently in place through its EU membership (covering about 15 percent of all UK trade).
    - UK exports to those countries revert to MFN rules for two years starting in mid-2019; UK imports do so either in mid-2019 or in mid-2020 depending on the temporary tariff regime.
    - The scenarios assume new trade agreements are secured after two years on terms similar to those currently in place.
  - Stricter immigration policies
    - Both scenarios assume a reduction in the net migration flow from the EU to the UK of 25,000 people per year until 2030, in line with the UK government’s intention to reduce net immigration.
    - For simplicity, net flow of migrants to the EU is assumed to increase by a similar amount.

### No-Deal Brexit: Scenario-Specific Assumptions (Trade, Border Disruption, Financial Conditions)
- Scenario Table (selected entries as described)
  - Baseline: No tariff increases; nontariff barriers gradually increase by 10 percent in tariff equivalent terms.
  - No-Deal Scenarios A and B: Tariffs increase by 4 percent in mid-2019 (mid-2020 for UK imports subject to temporary tariff regime); nontariff barriers increase gradually by an additional 14 percent (in tariff-equivalent terms) relative to baseline.
  - Trade with third countries under no-deal: The United Kingdom sets tariffs unilaterally to zero on 87 percent of its imports from mid-2019 to mid-2020; the United Kingdom loses access to most existing agreements, secures new agreements by 2021.
- Border disruption
  - Scenario A: No border disruptions.
  - Scenario B: Delays in customs-clearing despite preparatory measures raise import costs for UK firms and households and to a lesser extent for the EU.
  - Estimated GDP declines from trade disruptions in Scenario B:
    - UK GDP decline in first year: 1.4 percent
    - UK GDP decline in second year: 0.8 percent
    - EU GDP decline in first year: 0.2 percent
    - EU GDP decline in second year: 0.1 percent
- Financial conditions
  - Scenario A: small tightening — UK sovereign spreads increase by 12.5 basis points and UK corporate spreads increase by 20 basis points; no tightening in the EU or rest of world.
  - Scenario B: more severe tightening — UK sovereign spreads increase by 100 basis points and UK corporate spreads increase by 150 basis points.
  - Temporary increases in corporate spreads: European Union by 25 basis points; rest of the world by 15 basis points.
  - Monetary policy response: UK monetary policy is eased according to a Taylor-type reaction function; euro area constrained by the lower bound on nominal interest rates in conventional policy.

### Simulation Results: Short-Term Effects
- Scenario A
  - Immediate negative impact on UK foreign and domestic demand due to increased trade barriers.
  - Gradual three-year transition on the UK side eases short-term import cost increases.
  - Total negative effect on UK GDP (difference between Scenario A and baseline) is about 3.5 percent by 2021.
  - EU activity declines, with GDP down 0.5 percent by 2021; effects heterogeneous across EU countries.
  - Effects on other regions are negligible.
  - Global GDP decrease over the same period: 0.2 percent.
- Scenario B
  - Incorporates border disruptions and more severe financial tightening; larger short-term contractions in the UK and modest effects on the EU and global activity (see quantitative declines under “Border disruption” and “Financial conditions” above).

### Simulation Results: Long-Term Effects
- Identical long-term effects in both alternative no-deal scenarios relative to the April 2019 WEO baseline, driven by:
  - Trade barriers reducing returns to capital in the UK and EU, lowering desired capital stock and potential output — much larger in the UK.
  - Stricter immigration policies reducing UK labor force size and increasing EU labor force size.
- Quantified long-term effects (percent deviation from April 2019 WEO baseline)
  - United Kingdom potential output lower by almost 3 percent in the long term.
  - European Union potential output lower by about 0.3 percent in the long term.
  - World GDP down by 0.1 percent in the long term.
- Additional modelling notes
  - Simulations do not reflect full effects from Brexit already present in the current baseline.
  - Scenarios do not include additional productivity effects from higher trade costs, nor possible effects from capital outflows and additional exchange rate pressures.
  - Scenarios include a small, temporary real depreciation of the pound mainly due to accommodative monetary policy.

### Comparison with Other Studies
- Other studies focusing on long-term impact of Brexit relative to staying in the EU estimate negative output effects of 3 percent to 10 percent.
- Long-term results here are in the middle of that range once effects already in the current baseline (a long-term loss of 3 percent of GDP according to IMF (2018)) are included.

### Labor Market Dynamics in Selected Advanced Economies (Box 1.1): Key Findings
- During the 2017–18 cyclical upsurge in global growth, labor markets tightened in advanced economies such as Germany, Japan, the United Kingdom, and the United States.
- Headline unemployment rates declined; involuntary part-time employment dropped; labor force participation rates rose.
- Nominal wage growth picked up in these economies but remains below pre-crisis averages.
- Continued sluggishness in wage growth largely accounted for by weaker productivity growth since the crisis.
- Nominal wage growth has broadly tracked labor productivity growth; little evidence of sustained increases in unit labor costs.
- Limited pass-through from rising wage growth to consumer price inflation so far, even after sustained declines in unemployment.

### Global Forecast: Key Policy, Financial, and Commodity Assumptions
- Tariffs (as of September 2018 and subsequent assumptions)
  - US tariffs incorporated:
    - 25 percent tariff on $50 billion in imports from China (July and August 2018).
    - 10 percent tariff on an additional $200 billion in imports from China (September 2018); in light of recent negotiations, tariffs on $200 billion of US imports from China are assumed to stay at 10 percent.
    - Tariffs on solar panels, washing machines, aluminum, and steel announced in first half of 2018 are factored in.
  - China response: tariffs of 5–10 percent on $60 billion in imports from the United States.
- Fiscal policy
  - Fiscal policy is assumed expansionary across advanced economies in 2019 and expected to turn contractionary in 2020 as the US stimulus unwinds.
  - Fiscal policy assumed expansionary across emerging market and developing economies in 2019 (in part reflecting a projected fiscal stimulus in China), before turning contractionary in 2020.
- Monetary policy
  - US federal funds rate expected to increase to about 2.75 percent by the end of 2019, with one hike projected in 2019.
  - Policy rates assumed to remain at close to zero in Japan through 2020 and negative in the euro area until mid-2020.
- Financial conditions
  - Baseline assumes a gradual tightening of global financial conditions with relative intensity varying across economies.
- Commodity prices
  - Based on oil futures contracts, average oil prices are projected at $59.2 in 2019 and $59.0 in 2020 (down from $68.8 and $65.7, respectively, in the October 2018 WEO).
  - Oil prices are expected to remain in that range, reaching about $60 a barrel by 2023.
  - Metal prices are expected to increase.

_International Monetary Fund | April 2019_

### 2.4 percent year over year in 2019 and decline by

### 2.4 percent year over year in 2019 and decline by

### Global commodity price trends and forecasts
- IMF Primary Commodity Price Index declined by 6.9 percent between August 2018 and February 2019.
- Energy prices:
  - Energy prices fell sharply, driving most of the index decline, with energy prices down 17.0 percent between August 2018 and February 2019.
  - Baseline assumptions suggest average annual IMF average petroleum spot prices of $59.2 a barrel in 2019—a decrease of 13.4 percent from the 2018 average—and $59.0 a barrel in 2020.
  - Brent futures contracts indicate that Brent prices will stay at about $60 for the next five years (as of February).
  - US crude oil production averaged 10.9 million barrels a day (mbd) in 2018, an increase of 1.6 mbd over the previous year.
  - OPEC and non-OPEC oil exporters agreed to cut crude oil production by 0.8 mbd and 0.4 mbd, respectively, from their October 2018 level, starting in January 2019 for an initial six-month period.
- Metals:
  - Metal prices increased 7.6 percent between August 2018 and February 2019.
  - Iron ore prices increased 28.8 percent between August 2018 and February 2019.
  - Copper prices increased 4.1 percent between August 2018 and February 2019.
  - Aluminum fell 9.2 percent between August 2018 and February 2019.
  - Nickel dropped 5.4 percent between August 2018 and February 2019.
  - Zinc increased 7.8 percent between August 2018 and February 2019.
  - Cobalt declined by 49.3 percent between August 2018 and February 2019.
  - IMF annual base metal price index is projected to increase by 2.4 percent in 2019 (relative to its average in 2018) and decrease by 2.2 percent per year in 2020.
- Food:
  - The IMF’s food and beverage price index increased by 1.9 percent between August 2018 and February 2019.
  - Wheat prices decreased by 15.8 percent between August 2018 and February 2019.
  - Corn prices increased by 4.4 percent between August 2018 and February 2019.
  - Soybeans increased by 5.6 percent between August 2018 and February 2019.
  - Poultry prices increased by 3.9 percent between August 2018 and February 2019.
  - World sugar prices jumped by 23.7 percent between August 2018 and February 2019.
  - Cotton prices declined by 14.2 percent between August 2018 and February 2019.
  - Food prices are projected to decrease by 2.9 percent a year in 2019 and then increase by 2.1 percent in 2020.
- Short-term risks to commodity price outlook:
  - Upside risks for oil include geopolitical events in the Middle East, civil unrest in Venezuela, a tougher US stance against Iran and Venezuela, and slower-than-expected US production growth.
  - Downside risks for oil include stronger-than-expected US production and noncompliance among OPEC and non-OPEC countries, as well as trade tensions and weaker global growth.
  - Upside risks for metals include higher-than-expected metals demand from China and supply shortages from tighter environmental regulations; downside risks include faster moderation in global growth and Chinese slowdown.
  - Weather disruptions (including El Niño conditions) and the resolution of trade conflicts (notably between the United States and China) are upside risks for food prices.

### Growth and price forecast comparisons (selected figures)
- Global growth/price excerpts from the text:
  - “2.4 percent year over year in 2019 and decline by 2.2 percent in 2020 (compared with a decrease of 3.6 percent followed by a slight pickup of 0.4 percent in the October WEO).”
  - “Food prices are projected to decline 2.9 percent year over year in 2019 before increasing 2.1 percent in 2020 (compared with the projected increases of 1.7 percent and 0.3 percent in the October 2018 WEO).”

### Regional and spatial disparities (Box 1.3 highlights)
- Persistent within-country regional disparities:
  - Within-country disparities in per capita GDP are large; regional disparities in emerging markets are more pronounced than in advanced economies.
  - Regional disparities have been shrinking in emerging markets since the early 1990s but advanced economies saw convergence until the 1980s and divergence since.
  - A region’s relative position compared with the country average is closely correlated with its relative position 10 years earlier: the 10-year lag of normalized GDP per capita at the regional level predicts about three-quarters of the variation in normalized regional per capita GDP today.
- Potential causes and constraints on convergence:
  - Market failures, coordination failure, obstacles to factor mobility, large fixed costs of migration, liquidity constraints, house price behavior, differential impacts of globalization and automation, and selective migration by education and employment status can all limit regional convergence.
- Labor mobility trends:
  - Declining mobility in the United States, with interstate mobility at a historic low, aligns with a broader decline of within-country migration in advanced economies; migration has increased in emerging markets on average, though from very low levels.
- Political economy and welfare implications:
  - Large, persistent disparities impose costs on left-behind places and booming areas, can reduce trust, increase political polarization, and may have added significance where spatial divisions align with political and ethnic tensions.

*Source: World Economic Outlook: Growth Slowdown, Precarious Recovery, April 2019 (selected excerpts).*

### Introduction

### Introduction

### Why commodity prices matter for global activity
- Commodities represent about 17 percent of global trade and are fundamental production inputs.
- Commodity prices reflect both current and expected future demand and supply conditions because many commodities are storable and traded in liquid and deep markets.
- Price movements can swiftly incorporate news and changes in sentiment about global economic conditions.
- Commodity prices are useful to nowcast or even forecast global economic activity.

### Challenges in using commodity prices as indicators
- Commodity supply shocks and commodity-specific demand factors are prominent confounding influences and can obscure the link between commodity prices and global activity.
- Reverse causality is possible—especially for oil—potentially introducing countercyclicality.
- Some commodity time series are short (for example, start only in 1992), which can affect synchronization estimates.
- The presence of stationary and nonstationary series can make some statistics (for example, concordance) potentially misleading.

### Methodology and data
- Cycle dating: The business-cycle-dating procedure of Harding and Pagan (2002) (an adaptation of Bry and Boschan (1971)) is used to identify peaks and troughs in real commodity prices.
  - A candidate turning point is identified as a local maximum or minimum if the price in that month is either greater or less than the price in the two months before and the two months after.
  - The sequence of resulting candidate turning points is then required to alternate between peaks and troughs.
  - Each phase (expansion or contraction) must be at least 12 months long.
- Data panel: An unbalanced panel, starting in 1957, of 57 (real) commodity price series is used, falling into four categories: energy, metals, food and beverages, and raw agricultural materials.
- Price construction: All commodity price series are monthly averages from the IMF’s Primary Commodity Price System, denominated in US dollars and divided by US consumer price inflation.
- Trend extraction for activity series: A Hodrick-Prescott filter with a very low lambda is used to extract a stable trend from global industrial production and GDP; quarterly GDP data have been interpolated monthly.
- Factor extraction: To isolate movements in commodity prices driven by global economic activity, a factor model is estimated at monthly frequency using principal components.

### Cyclicality and comovement of commodity prices — key findings
- Most commodities show asymmetric phases characterized by longer and dull contractions punctuated by sharp expansions.
- Energy commodities stand out with the longest and sharpest phases; a full energy cycle tends to last slightly less than four years.
- The interaction of commodity supply shocks with storage demand is an important driver of commodity price movements; supply shocks when inventories or spare capacity are low tend to cause price spikes.
- Bellwethers of global industrial production are mostly base metals (such as zinc, copper, and tin) and, to a lesser extent, energy and fertilizers.
- Propane shows the highest synchronization with global industrial production (noting its time series, and that for natural gas, start only in 1992 and hence are shorter).
- Agricultural prices, especially food prices, are, on average, only modestly in sync with economic activity.
- Food and beverage commodities tend to be more synchronized to global GDP than to industrial production because income, rather than production, plays a more relevant role in their demand (example: arabica coffee).

### Concordance and commodity-wide synchronization
- The synchronization metric used is the concordance, which calculates the share of time two series are in the same phase (Harding and Pagan 2002).
  - Concordance is bounded between 0 and 1; two independent random walks have a concordance of 0.5.
  - A value of 1 (–1) means that all commodity prices are expanding (contracting) simultaneously—perfect synchronization—while a value of 0 implies that half of commodity prices are in the same phase, lowest synchronization.
- Commodity-wide concordance (the share of commodities that are in the expansion or contraction phase) typically peaks (or troughs) when activity is expanding (or contracting) most, and thus anticipates turning points of economic activity.
- This finding highlights the presence of common latent factor(s) related to global activity that drive commodity prices.

### Selected quantitative cycle statistics (as presented)
- Table 1.SF.1. Commodity Price Cycle Descriptive Statistics (presented in the source):
  - Energy: 202464.7262.813.373.01
  - Base Metals: 182455.1957.983.052.41
  - Food and Beverages: 162045.2549.602.802.33
  - Agricultural Raw Materials: 182243.2746.702.462.00
- Note: In the source, Duration measures the average length (in months) of a price phase (expansion or contraction). Amplitude measures the average price change (in percentage terms) from trough to peak in case of an expansion, and from peak to trough in case of a contraction. Sharpness measures the average price increase per month (in percentage terms) experienced during an expansion, and the average price decline during a contraction. All statistics are calculated by averaging over all commodities in a particular group.

### Implications for nowcasting and forecasting
- The presence of common latent global-demand-related factors in commodity prices suggests these prices can be exploited to nowcast and forecast movements in the global business cycle.
- The analysis proceeds to extract global factors from commodity price comovement via principal components and to test whether the extracted global factors have nowcasting and predictive power for economic activity.

*Source: IMF — Introduction (text - Introduction)*

### 2. Lower Synchronization

### 2. Lower Synchronization

### Commodity synchronization with global cycles
- Synchronization is defined as the concordance between the price cycle of a given commodity and the business cycle (de-trended GDP or IP) using Harding and Pagan’s (2002) procedure.
- Concordance calculates the share of time two series are in the same phase; a concordance above 0.5 denotes a positive synchronization.
- Bars in the figures represent synchronization with de-trended global industrial production (IP) (darker bars) and GDP (lighter bars).
- Commodity-wide concordance is presented (left scale) alongside Global industrial production (right scale).
- WTI = West Texas Intermediate.

### Latent factors extracted from commodity prices
- Rationale: Supply- and commodity-specific demand shocks make commodity prices diverge; estimating latent factors that cause commodity prices to comove provides a proxy for global economic activity.
- Practical note: It may be preferable to exclude commodities that behave more like financial assets (for example gold and silver) or those that are too closely related (for example soybean meal and soybean oil).
- Estimation approach: Log differences of prices (divided by the US consumer price index) have been z-scored. The use of log-detrended or log differences is less relevant for the estimation.
- Empirical finding: The first two extracted factors explain about 20 percent of the variance in commodity price monthly changes. The relevance of the remaining factors drops off quickly and is not statistically related to economic activity.
- Interpretation of factors:
  - First factor: a global factor that is visually closely related to global GDP when cumulated.
  - Second factor: a relative-price factor representing a negative demand shift for agricultural products relative to energy and metals.
- Correlation: When cumulated, the first and second latent factors show a positive correlation, 0.67.
- Split-sample insight: First factors are also extracted by splitting the sample into agricultural and nonagricultural (energy and metals) commodities; the global factor and the relative-price factor are well approximated by a linear combination of the two first factors of the split subsamples.
- Regression fit: A regression of the global (relative-price) factor on the first factors extracted from the agriculture and nonagriculture samples separately yields an R-squared of 0.99 (0.88).
- Additional note: The (negative of the) first factor in levels mimics movements in the US dollar real effective exchange rate (REER), but this association weakens at higher frequencies and when noncommodity currencies are excluded.

### Nowcasting global activity using commodity-based latent factors
- Motivation: First releases of global industrial production lag by two months and GDP lags by one quarter; both are often substantially revised, so latent factors from commodity prices may help nowcast global activity.
- Nowcasting specifications tested (following Stock and Watson 2002):
  - Benchmark: autoregressive (AR)(p) process with optimal lag.
  - Specification 1: only the global factor (first principal component).
  - Specification 2: global and relative factors (first two principal components).
  - Specification 3: first principal components of agricultural and nonagricultural commodities (split sample).
- Sample periods:
  - Global industrial production nowcast: January 1980 to December 2018.
  - Global GDP nowcast: 1980:Q1 to 2018:Q3.
- Industrial production nowcast (monthly frequency) results (Table 1.SF.2):
  - Benchmark RMSE: 0.55%
  - Specification 1 RMSE: 0.54%
  - Specification 2 RMSE: 0.53%
  - Specification 3 RMSE: 0.54%
  - Benchmark-to-specification RMSE Ratios: 1.0, 0.99, 0.97, 0.98 (as presented)
- Global GDP nowcast (Table 1.SF.3) — one-month, two-month, and quarter information:
  - Benchmark RMSE: 0.42% (one-month information)
  - Specification 1 RMSE (One Month Information): 0.38%
  - Specification 2 RMSE (One Month Information): 0.37%
  - Specification 3 RMSE (One Month Information): 0.38%
  - Ratios (one month): 1.0, 0.90, 0.90, 0.90
  - Two Months Information RMSEs: Benchmark 0.42%; Specification 1 0.36%; Specification 2 0.36%; Specification 3 0.36%
  - Two Months Ratios: 1.0, 0.87, 0.86, 0.86
  - Quarter Information RMSEs: Benchmark 0.42%; Specification 1 0.36%; Specification 2 0.35%; Specification 3 0.35%
  - Quarter Ratios: 1.0, 0.86, 0.84, 0.85
- Key empirical messages:
  - Introducing the global factor and the relative-price factor increases the ability to nowcast industrial production relative to the AR(p) benchmark.
  - Nowcasting improvements are modest for monthly industrial production growth due to volatility, but more pronounced for GDP nowcasts.
  - For GDP, the improvement in root mean square error relative to the AR(p) benchmark is 10 percent with only the global factor from one month of commodity price information and increases to 15 percent when the quarter is completed.
  - R-squared for the GDP nowcast model is about 0.48.
  - Commodity prices are mostly informative during periods of high economic volatility, when the AR(p) process performs poorly.

### Forecasting global activity using commodity-based latent factors
- Forecast evaluation approach:
  - Out-of-sample forecast performance using recursive estimation.
  - Estimation sample for forecasting: 1980–98; forecasts generated for 2000–18.
  - Forecast horizons: one-month-ahead and three-month-ahead industrial production; one-quarter-ahead GDP.
  - Forecast performance measured by root mean squared forecast error (RMSE) and relative RMSE (Ratio = RMSE divided by benchmark RMSE).
- Global industrial production forecasting results (Table 1.SF.4):
  - IP Month RMSEs: Benchmark 0.55%; Specification 1 0.50%; Specification 2 0.49%; Specification 3 0.50%
  - IP Ratios: 1.0, 0.92, 0.90, 0.92
- GDP forecasting results (Table 1.SF.4) — information availability one, two, or three months into the quarter:
  - GDP One Month Information RMSEs: Benchmark 0.51%; Specification 1 0.50%; Specification 2 0.51%; Specification 3 0.51%
  - One Month Ratios: 1.0, 0.99, 1.00, 1.00
  - GDP Two Months Information RMSEs: Benchmark 0.51%; Specification 1 0.48%; Specification 2 0.48%; Specification 3 0.48%
  - Two Months Ratios: 1.0, 0.95, 0.95, 0.95
  - GDP Quarter Information RMSEs: Benchmark 0.51%; Specification 1 0.46%; Specification 2 0.46%; Specification 3 0.46%
  - Quarter Ratios: 1.0, 0.91, 0.91, 0.90
- Additional forecasting insights:
  - All specifications improve the one-month-ahead global industrial production forecast relative to the benchmark; Specification 2 (two factors) does best and improves the forecast by 10 percent.
  - The one-quarter-ahead GDP forecast is improved as price information in the quarter becomes available; when the full quarter is available, the RMSE of the next-quarter GDP is improved by almost 10 percent relative to the benchmark.
  - Factor lags are significant, allowing testing of predictive content for global activity.

### Conclusion and policy-relevant implications
- There is a wealth of information embedded in commodity prices that is useful for gauging global economic activity once idiosyncratic factors are removed.
- Major movements in prices of base metals, and to some extent energy and agricultural products, convey information about the state of the global economy, especially during periods of significant fluctuations when forecasting and nowcasting are most needed.
- Commodity-price-based latent factors provide timely indicators useful for nowcasting and short-term forecasting of industrial production and GDP, improving performance relative to autoregressive benchmarks in many specifications.

_©International Monetary Fund. Not for Redistribution_

### Annex Table 1.1.3. Western Hemisphere Economies: Real GDP, Consumer Prices, Current Account Balance, and Unemployment

### Annex Table 1.1.3. Western Hemisphere Economies: Real GDP, Consumer Prices, Current Account Balance, and Unemployment

### Overview
- Variables and units presented:
  - Real GDP: Annual percent change.
  - Consumer Prices: Movements shown as annual averages.
  - Current Account Balance: Percent of GDP.
  - Unemployment: Percent. National definitions of unemployment may differ.
- Aggregate and country projections cover 2018, 2019, and 2020.
- Note: Aggregates exclude Venezuela. Data for some countries are based on fiscal years.

### North America (aggregate and selected economies)
- North America (Real GDP; Consumer Prices; Current Account Balance; Unemployment)
  - Real GDP: 2.7 (2018), 2.2 (2019), 1.9 (2020)
  - Consumer Prices: 2.7 (2018), 2.2 (2019), 2.7 (2020)
  - Current Account Balance: –2.3 (2018), –2.4 (2019), –2.6 (2020)
  - Unemployment: . . . (2018), . . . (2019), . . . (2020)
- United States
  - Real GDP: 2.9 (2018), 2.3 (2019), 1.9 (2020)
  - Consumer Prices: 2.4 (2018), 2.0 (2019), 2.7 (2020)
  - Current Account Balance: –2.3 (2018), –2.4 (2019), –2.6 (2020)
  - Unemployment: 3.9 (2018), 3.8 (2019), 3.7 (2020)
- Canada
  - Real GDP: 1.8 (2018), 1.5 (2019), 1.9 (2020)
  - Consumer Prices: 2.2 (2018), 1.7 (2019), 1.9 (2020)
  - Current Account Balance: –2.6 (2018), –3.1 (2019), –2.8 (2020)
  - Unemployment: 5.8 (2018), 5.9 (2019), 6.0 (2020)
- Mexico
  - Real GDP: 2.0 (2018), 1.6 (2019), 1.9 (2020)
  - Consumer Prices: 4.9 (2018), 3.8 (2019), 3.1 (2020)
  - Current Account Balance: –1.8 (2018), –1.7 (2019), –1.9 (2020)
  - Unemployment: 3.3 (2018), 3.5 (2019), 3.6 (2020)
- Puerto Rico (territory; statistics maintained separately)
  - Real GDP: –2.3 (2018), –1.1 (2019), –0.7 (2020)
  - Consumer Prices: 2.5 (2018), 0.3 (2019), 1.3 (2020)
  - Current Account Balance: . . . (2018), . . . (2019), . . . (2020)
  - Unemployment: 11.0 (2018), 11.0 (2019), 11.2 (2020)

### South America (aggregate and selected economies)
- South America (aggregate)
  - Real GDP: 0.4 (2018), 1.1 (2019), 2.4 (2020)
  - Consumer Prices: 7.1 (2018), 8.1 (2019), 6.1 (2020)
  - Current Account Balance: –1.8 (2018), –1.9 (2019), –1.9 (2020)
  - Unemployment: . . . (2018), . . . (2019), . . . (2020)
- Brazil
  - Real GDP: 1.1 (2018), 2.1 (2019), 2.5 (2020)
  - Consumer Prices: 3.7 (2018), 3.6 (2019), 4.1 (2020)
  - Current Account Balance: –0.8 (2018), –1.7 (2019), –1.6 (2020)
  - Unemployment: 12.3 (2018), 11.4 (2019), 10.2 (2020)
- Argentina
  - Real GDP: –2.5 (2018), –1.2 (2019), 2.2 (2020)
  - Consumer Prices: 34.3 (2018), 43.7 (2019), 23.2 (2020)
  - Current Account Balance: –5.4 (2018), –2.0 (2019), –2.5 (2020)
  - Unemployment: 9.2 (2018), 9.9 (2019), 9.9 (2020)
- Colombia
  - Real GDP: 2.7 (2018), 3.5 (2019), 3.6 (2020)
  - Consumer Prices: 3.2 (2018), 3.4 (2019), 3.2 (2020)
  - Current Account Balance: –3.8 (2018), –3.9 (2019), –3.8 (2020)
  - Unemployment: 9.7 (2018), 9.7 (2019), 9.5 (2020)
- Venezuela
  - Real GDP: –18.0 (2018), –25.0 (2019), –10.0 (2020)
  - Consumer Prices: 929,789.5 (2018), 10,000,000 (2019), 10,000,000 (2020)
  - Current Account Balance: 6.0 (2018), 1.4 (2019), –1.9 (2020)
  - Unemployment: 35.0 (2018), 44.3 (2019), 47.9 (2020)
- Chile
  - Real GDP: 4.0 (2018), 3.4 (2019), 3.2 (2020)
  - Consumer Prices: 2.3 (2018), 2.3 (2019), 3.0 (2020)
  - Current Account Balance: –3.1 (2018), –3.2 (2019), –2.8 (2020)
  - Unemployment: 6.9 (2018), 6.5 (2019), 6.2 (2020)
- Peru
  - Real GDP: 4.0 (2018), 3.9 (2019), 4.0 (2020)
  - Consumer Prices: 1.3 (2018), 2.4 (2019), 2.0 (2020)
  - Current Account Balance: –1.5 (2018), –1.4 (2019), –1.5 (2020)
  - Unemployment: 6.7 (2018), 6.6 (2019), 6.5 (2020)
- Uruguay
  - Real GDP: 2.1 (2018), 1.9 (2019), 3.0 (2020)
  - Consumer Prices: 7.6 (2018), 7.6 (2019), 7.2 (2020)
  - Current Account Balance: –0.6 (2018), –0.8 (2019), –1.2 (2020)
  - Unemployment: 8.0 (2018), 8.1 (2019), 7.9 (2020)
- Paraguay
  - Real GDP: 3.7 (2018), 3.5 (2019), 4.0 (2020)
  - Consumer Prices: 4.0 (2018), 3.6 (2019), 4.0 (2020)
  - Current Account Balance: 0.5 (2018), –0.8 (2019), 0.4 (2020)
  - Unemployment: 5.6 (2018), 5.7 (2019), 5.8 (2020)

### Central America and the Caribbean (aggregates)
- Central America (aggregate)
  - Real GDP: 2.7 (2018), 3.2 (2019), 3.5 (2020)
  - Consumer Prices: 2.6 (2018), 2.7 (2019), 3.0 (2020)
  - Current Account Balance: –3.6 (2018), –2.9 (2019), –2.7 (2020)
  - Unemployment: . . . (2018), . . . (2019), . . . (2020)
- Caribbean (aggregate)
  - Real GDP: 4.7 (2018), 3.6 (2019), 3.7 (2020)
  - Consumer Prices: 3.7 (2018), 2.4 (2019), 4.3 (2020)
  - Current Account Balance: –2.3 (2018), –2.3 (2019), –2.0 (2020)
  - Unemployment: . . . (2018), . . . (2019), . . . (2020)

### Memoranda and regional aggregates
- Latin America and the Caribbean (aggregate)
  - Real GDP: 1.0 (2018), 1.4 (2019), 2.4 (2020)
  - Consumer Prices: 4.2 (2018), 6.5 (2019), 5.1 (2020)
  - Current Account Balance: –1.9 (2018), –1.9 (2019), –2.0 (2020)
  - Unemployment: . . . (2018), . . . (2019), . . . (2020)
- East Caribbean Currency Union
  - Real GDP: 2.1 (2018), 4.0 (2019), 3.1 (2020)
  - Consumer Prices: 1.3 (2018), 1.6 (2019), 2.0 (2020)
  - Current Account Balance: –10.5 (2018), –9.6 (2019), –9.4 (2020)
  - Unemployment: . . . (2018), . . . (2019), . . . (2020)

### Notes and data caveats (as presented in the table)
- Movements in consumer prices are shown as annual averages. Aggregates exclude Venezuela.
- Year-end to year-end changes can be found in Tables A6 and A7 in the Statistical Appendix.
- Current account balance is percent of GDP.
- Unemployment is percent; national definitions may differ.
- Puerto Rico is a territory of the United States but its statistical data are maintained on a separate and independent basis.
- Central America comprises Belize, Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, and Panama.
- The Caribbean comprises Antigua and Barbuda, Aruba, The Bahamas, Barbados, Dominica, Dominican Republic, Grenada, Haiti, Jamaica, St. Kitts and Nevis, St. Lucia, St. Vincent and the Grenadines, and Trinidad and Tobago.
- Latin America and the Caribbean comprises Mexico and economies from the Caribbean, Central America, and South America.

*International Monetary Fund. Annex Table 1.1.3, Western Hemisphere Economies (extracted from the provided chapter table).*

### Introduction

### Introduction

### Context and observed macroeconomic trends
- Public debate about rising corporate power is mounting amid the rise of corporate giants and broader macroeconomic trends in advanced economies over the past three decades.
- Five worrisome macroeconomic trends highlighted:
  - sluggish investment despite falling borrowing costs and rising expected returns from investment, as captured by Tobin’s Q;
  - a growing disconnect between a roughly stable rate of return on productive capital and a falling rate of return on safer assets, such as the bonds of governments and the healthiest firms;
  - a widening gap between financial and productive wealth;
  - falling labor income shares and rising income inequality;
  - the slowdown in productivity growth (Adler and others 2017).

### Research questions and data
- The chapter investigates whether rising corporate market power could be a factor behind slowing trend growth and growing inequality, and how it relates to other proposed drivers (for example, slowing pace of major inventions; protracted weak demand; mismeasured intangible capital; falling investment prices; growing demand for safe assets; weaker worker bargaining power).
- Data and scope:
  - The analysis looks at close to 1 million firms covering large swaths of the economy across 27 countries—about two-thirds advanced economies and one-third emerging market economies.
  - The final cleaned data set includes more than 900,000 distinct firms.
  - Countries included are listed in the chapter (27-country sample).
- Core questions tackled:
  - Has corporate market power increased globally? How do trends differ across country income groups, countries, industries, and firms?
  - What might be the drivers of rising market power—changes in product market structure (including the digital economy) versus policy-driven weakening of competition?
  - What is the impact of market power on growth and income distribution—effects on investment, innovation, and labor income shares?
  - What are the policy implications and macroeconomic implications (for example, for monetary policy)?

### Measurement and methodology
- Two main definitions of market power considered:
  - Price markups: the ratio of price to marginal cost (main measure used throughout the chapter).
  - Economic rents: operational profitability measures such as the ratio of operating earnings to sales (Lerner index).
- Limitations noted:
  - Markups may overestimate market power in the presence of fixed costs that must be recouped.
  - Lerner indices capture average—not marginal—cost wedges and can be volatile.
  - Market concentration measures are computed (share of top firms in total sales in narrowly defined four-digit NACE industries) but should be interpreted with caution.
- Empirical approach:
  - Markups and Lerner indices computed for each firm, then aggregated to industry or country level.
  - Concentration indices computed for narrowly defined industries in each country.
  - Markups measured following De Loecker and Warzynski (2012) as the ratio of a firm’s output elasticity of a variable input to the share of that input in total revenue.

### Key findings
- Aggregate market power trends:
  - Across the 27 sample countries, the (firm-revenue-weighted) average markup increased by 6 percent during 2000–15.
  - In level terms, the (firm-revenue-weighted) average markup shows an increase from about 1.28 in 2000 to 1.36 in 2015 (corresponding to a markup of the price over marginal cost of 28 percent in 2000 and 36 percent in 2015).
  - Average profitability, as measured by the Lerner index, also increased throughout the sample period.
  - Market concentration has increased to a lesser extent.
- Differences across country groups and industries:
  - The rise in markups is strongly concentrated among advanced economies: average markup rose by about 7.7 percent throughout 2000–15 in advanced economies versus only 1.8 percent for the group of emerging market economies covered.
  - Markup increases have been fairly broad based across countries and industries—taking place in almost all advanced economies and nearly two-thirds of country-industry pairs—but the magnitude varies (for example, larger in the United States than across the European Union).
  - The increase is essentially concentrated in nonmanufacturing industries.
- Firm-level patterns:
  - A key contributor is the increase in markups charged by a small fraction of firms. Most of these firms are rather small, but the larger ones in the group account for the vast majority of the group’s total revenue.
  - High-markup firms exhibit higher productivity and are more likely to invest in intangible assets (patents, software).
  - In the United States, high-markup firms gained market share during 2000–15, contributing to a larger increase in aggregate markups relative to other countries—consistent with a productivity-enhancing growth of high-productivity, high-markup firms at the expense of low-productivity, low-markup firms.
- Drivers and interpretation:
  - Evidence tentatively suggests changes in product market structure (winner-takes-most dynamics, specific intangible assets, network effects, economies of scale) underpinned at least some of the overall rise in market power.
  - The broad-based nature of increasing markups and the role of a small fraction of firms hint at common forces rather than solely policy-driven weakening of competition.
  - Weak pro-competition policies can magnify winner-takes-most dynamics, and dominant firms may attempt to entrench positions by erecting barriers to entry.
- Macroeconomic effects:
  - Impact on growth has been modest so far but could worsen if market power of high-markup firms rises further.
  - Higher markups have been associated with somewhat weaker investment despite higher profits and Tobin’s Q.
    - Empirical estimates suggest that because of this investment channel, output would be about 1 percent higher today in the average advanced economy if markups had not increased since 2000—ignoring effects from technological or organizational improvements that may have enabled some firms to raise markups.
  - Through the investment channel, rising market power may have slightly reduced the natural (real) rate of interest, making the effective lower bound on policy interest rates more binding.
  - Effects on innovation are ambiguous: may have been marginally positive so far but could turn increasingly negative if high-markup firms further increase market power.
  - Higher markups can spill over through supply-chain links: higher markups across foreign suppliers have been associated with slightly lower output among emerging market firms that purchase inputs in less competitive markets.
  - Rising market power during 2000–15 reduced labor shares of income by a minimum of 0.2 percentage point—about 10 percent of the overall decline—across advanced economies. This lower-bound estimate includes only within-firm markup effects and ignores reallocation and unequal firm-level market-power gains that can affect wage and wealth inequality.

### Policy implications
- With mounting risks to growth and income distribution, policymakers should keep future market competition strong.
- Recommended reforms include:
  - cutting domestic barriers to entry in nonmanufacturing industries;
  - liberalizing trade and foreign direct investment;
  - adjusting competition policy frameworks to address emerging issues as needed;
  - easing obstacles to technological catchup by lagging firms;
  - shifting the burden of corporate taxation onto economic rent.

*Source: Introduction, "The Rise of Corporate Market Power and Its Macroeconomic Effects," Chapter 2, World Economic Outlook: Growth Slowdown, Precarious Recovery, International Monetary Fund, April 2019.*

### 1. Markups

### 1. Markups

### Evolution of Market Power
- All measures point toward a moderate increase in market power over time: higher markups, higher profitability, and, to a lesser extent, higher concentration.
- Markup calculations: based on the approach of De Loecker and Warzynski (2012) using the Orbis database; regressions include year fixed effects and country fixed effects and are weighted by firms’ operating revenue.
- Profitability measure: Lerner index, computed as the weighted average of firms’ ratio of earnings before taxes to revenue.
- Concentration measure: ratio of sales of top four to top 20 firms within each country-sector bin; aggregation via simple averages across sectors within a country, then the median across countries.
- Summary observation: the aggregate rise in markups is moderate since 2000 across advanced economies, with larger increases in the United States (twice as large as in the average advanced economy).

### Distribution Across Countries, Industries, and Firms
- Markup increases are concentrated in advanced economies; markups in the selected emerging markets covered by the analysis have risen only slightly.
- Industry patterns:
  - Nearly two-thirds of country-industry pairs in the sample show markup increases.
  - Largest increases among nonmanufacturing industries and in industries that use digital technologies most intensively.
  - The average markup across manufacturing industries has been mostly flat.
- Decomposition of aggregate markup increases (Melitz-Polanec decomposition):
  - Two-thirds of the overall markup increase can be accounted for by incumbent firms (intensive margin) and the remainder by net entry of new firms (extensive margin).
  - Among incumbents, the rise in markups reflects primarily an increase within firms rather than reallocation of market shares (within component large and positive; reallocation component small or negative).
  - United States exception: reallocation component accounted for about 80 percent of the rise in the aggregate markup.
  - New firms entering with high markups contributed about one-third of the overall rise in markups across advanced economies (entry component).
- Heterogeneity across firms:
  - Markup increases have been largely concentrated in the top 10 percent of the markup distribution.
  - Firms in the top decile increased their (weighted) average markup by more than 30 percent, while the remaining nine deciles report a (weighted) average increase of just 2 percent.
  - Sector representation in the top decile (by revenue): information and communication; financial and insurance activities; manufacturing; utilities.
  - Likelihood above cross-sector average of being in the top decile: information and communication; finance and insurance activities; utilities.
  - Likelihood below cross-sector average: construction; manufacturing; wholesale and retail trade.
  - Size and revenue composition of top-decile firms:
    - Most top-decile firms are small—in the bottom half of the size (revenue) distribution—but the larger firms within the top decile account for the vast majority of the group’s total revenue.
  - Performance differentials (top 10 percent vs other 90 percent):
    - About 50 percent more profitable.
    - More than 30 percent more productive.
    - More than 30 percent more intensive in use of intangible assets.

### Macroeconomic Implications: Innovation
- Empirical strategy:
  - Cross-country firm- and industry-level regressions linking patents to lagged markups and markup squared, controlling for rich fixed effects and using instrumental variables (median markup of other firms in same country-industry-year) to address reverse causality.
  - Innovation proxied by patenting activity (various indicators).
- Hump-shaped relationship between markups and patents:
  - At low markup levels, higher markups increase patents; beyond a turning point, further markup increases reduce patents.
  - At the industry level over the sample period, more than 80 percent of observations were located before the turning point in 2000; the fraction beyond the turning point increased from roughly 15 percent in 2000 to 21 percent in 2015.
  - At the firm level, about 7.5 percent of firms were located beyond the turning point in 2015; that share increased by 50 percent during the sample period.
- Implications from estimates (take empirical estimates at face value):
  - Past overall markup increases (2000–15) are estimated to have had a marginally positive effect on patents for the full sample.
  - If markups rise in 2015–30 at the same rate as in 2000–15:
    - Predicted patent stock of high-markup firms (top decile) would be almost 4 percent lower than if markups were stable.
    - Overall patent stock would be more than 0.3 percent lower than if markups were stable.
- Concern: firms in the top decile are, on average, already beyond the turning point; further strengthening of market power among these firms could increasingly depress innovation.

### Macroeconomic Implications: Physical Capital Investment and Aggregate Effects
- Background:
  - Private fixed investment declined by about 25 percent, on average, across advanced economies since the global financial crisis compared with its precrisis trend.
  - Possible contributing factors include weak growth, credit constraints, shifts toward intangibles, and increased market power.
- Mechanism:
  - As market power increases, firms charge higher prices and reduce output at a given marginal cost; reduced desired output lowers demand for capital and investment; long-term effect can reduce capital-to-output ratio.
- Empirical findings on investment:
  - Firm-level analysis (net investment rate in tangible assets explained by lagged markup with controls and instruments) finds a monotonic negative relationship between markups and investment.
  - Main quantitative result: a 10 percentage point increase in a firm’s markup is associated with a statistically significant 0.6 percentage point decrease in its physical capital investment rate.
  - Aggregate implications illustrated by simulations:
    - For the overall sample, the average increase in firms’ markups since 2000 is associated with a 0.4 percentage point decrease in the investment rate.
    - For top decile firms, the average increase in markups is associated with a 2 percentage point decrease in the investment rate.
    - Counterfactual simulation for average advanced economy in sample:
      - If markups had remained at 2000 levels, the physical capital stock in 2015 would be about 3 percent larger.
      - That would have translated into an output gain of about 1 percent (assuming the elasticity used in the exercise).
- Overall implication: rising markups have contributed to some reduction in firms’ physical capital investment since the early 2000s, with measurable effects on aggregate capital and output in advanced economies.

*Sources: Orbis; PATSTAT (Worldwide Patent Statistical database); and IMF staff calculations.*

### 0.4 percentage point decrease in the physical capital investment rate. For the firms

### 0.4 percentage point decrease in the physical capital investment rate. For the firms

### Investment effects of higher markups
- A 0.4 percentage point decrease in the physical capital investment rate is associated with firms’ average markup increases (within-firm effect).
- For the firms in the top decile of the markup distribution, the (larger) average increase in firms’ markups is associated with a decrease in the investment rate of 2 percentage points.
- The estimated magnitude in the predicted loss in physical capital is somewhat below, but close to, that obtained when simulating the macroeconomic model used in the chapter’s subsequent subsection.
- The empirical analysis focuses on within-firm effects; between-firm effects (reallocation of capital between firms with different markup levels) were investigated and found to have typically been small.

### International spillovers through supply chains
- Higher domestic markups can reduce demand for foreign inputs (demand channel) and raise the price of intermediate goods sold to foreign firms (input channel).
- Regressions of a country-industry’s value added on weighted averages of foreign buyers’ and foreign suppliers’ markups (controlling for domestic links and fixed effects) indicate moderate negative international spillovers through the input channel.
- Example: For a hypothetical industry in an emerging market economy that imports 40 percent of its value added, a 10 percentage point markup increase across all its foreign suppliers is found to reduce output by 0.3 percent, all else equal.

### Model simulations — Economic slack, interest rates, and inflation
- The chapter uses an estimated dynamic stochastic general equilibrium model of the euro area and the United States, calibrated to match the within-firm component of the observed trend in markups since 2000.
- Rising markups are modeled as a decline in the substitutability between goods and services produced by different firms.
- A sustained, unexpected rise in markups is inflationary as firms raise prices, but there is an offsetting contractionary force: firms cut output and investment to earn higher profits, magnified by nominal rigidities.
- For the euro area and the United States as a group, by 2015 the model suggests:
  - The output gap might have been about 0.3 percentage point wider than if markups had stayed at their 2000 level.
  - Inflation about 0.2 percentage point higher.
  - The natural interest rate about 10 basis points lower.
- Figure 2.9 result: The trend rise in markups since 2000 may be associated with a 0.1 percentage point reduction in the net investment rate and a 10 basis point reduction in the annual natural interest rate by 2015.

### Effects on the responsiveness of inflation (Phillips curve)
- The impact of rising market power on the responsiveness of inflation to economic conditions is ambiguous and depends on firms’ price-setting behavior.
- Model simulations suggest the implied change in responsiveness of inflation to economic conditions has been small, largely because the increase in markups has not been large enough so far.

### Income distribution and labor shares
- After remaining largely stable for decades, the share of national income paid to labor has fallen since the 1980s across many advanced economies, by an average of about 2 percentage points.
- Empirical cross-country firm-level regressions (instrumenting markups) imply that an increase in markups of 10 percentage points is associated with a statistically significant 0.3 percentage point decrease in the labor share (ratio of firm’s wage bill to value added).
- Figure 2.10 illustrates:
  - For the overall sample, the average increase in firms’ markups since 2000 is associated with a 0.2 percentage point decrease in the labor share.
  - For the sample of top decile firms, the average increase in markups is associated with a decrease in the labor share of 1 percentage point.
- Taken at face value, rising markups have accounted for at least 10 percent of the trend decline in the labor share in the average advanced economy.
- Without any markup increases since 2000, the average labor share across the sample of advanced economies might have been at least 0.2 percentage point higher today; this compares with an average fall in the labor share of about 2 percentage points over the past two decades.
- The within-firm analysis likely underestimates the overall effect where between-firm resource reallocation (high-markup firms gaining share at expense of low-markup firms) also contributes to aggregate labor share declines.

### Innovation and other macroeconomic implications
- The empirical analysis highlights higher markups’ harm on investment and their broadly neutral effect on innovation to date; the mixed impact on innovation could turn increasingly negative with increased market power of high-markup firms.
- Rising markups in advanced economies may have entailed mild adverse spillovers to emerging markets.
- Because rising markups foster some economic slack and slightly lower the natural interest rate, they can deepen a recession when policy interest rates hit the effective lower bound, potentially amplifying recessions or pushing central banks toward unconventional policies.

### Summary and policy implications
- Over the past two decades, a generally moderate but broad-based rise in corporate market power has been observed across advanced economies, driven primarily by a small fraction of firms.
- Macroeconomic implications have been rather modest so far but would become increasingly negative if the market power of high-markup firms continues to rise: investment would weaken, innovation could slow, labor income shares would fall further, and monetary policymakers might find it more difficult to stabilize output during major downturns.
- Evidence tentatively points to technology-driven changes in product market structure underpinning at least some of the rise in market power: winner-takes-most dynamics linked to intangible assets, network effects, and economies of scale.
- Other factors that may magnify market power increases include weaker adaptation of competition policy (for example, merger enforcement or exclusionary conduct), and mergers and acquisitions have been followed by significantly higher markups in the sample analyzed.
- The extent to which gains from economies of scale or other efficiencies offset losses to consumers from higher markups remains an open question.

*Source: Chapter 2, "The Rise of Corporate Market Power and Its Macroeconomic Effects," IMF World Economic Outlook, April 2019.*

### CHAPTER 2

### CHAPTER 2

### Overview: Rise of Corporate Market Power and Policy Implications
- Calls for structural reforms to keep product market competition strong, particularly in nonmanufacturing industries.
- Strengthening market contestability by cutting domestic regulatory barriers to entry (such as administrative burdens on start-ups or regulatory protections of incumbents) and further openness to trade and foreign direct investment would make markets more contestable by increasing the threat of entry and help spur growth.
- Competition law and policy are key complements to product market deregulation; resources and powers for competition authorities to investigate mergers, undertake market examinations, and enforce strong remedies (including divestiture) are emphasized.
- Dynamic perspective recommended: the larger and more persistent an industry’s profits, the more likely barriers to entry exist and the greater the need for close examination of the industry.
- Easing obstacles to technological catch-up by lagging firms could strengthen competition (examples include well-calibrated intellectual property rights and competition-neutral data governance regimes).
- Corporate taxation reform is motivated by rising market power:
  - A regular corporate income tax taxes both excess returns (economic rents) and normal returns.
  - Efficient corporate taxation would exempt normal returns and focus on economic rents only; achievable through cash flow taxes (allowing investment to be expensed) or by providing an allowance for corporate equity (a deduction equal to the normal return on equity).
  - Innovation that generates economic rents can be encouraged through incentives, such as research and development tax credits.
  - The destination-based version of these taxes taxes corporate income based on the location of final consumption rather than the origin of profits and helps withstand profit shifting by multinational firms.

### Box 2.1 — Comovement between Industry Concentration and Corporate Saving (G7 listed firms)
- Context: Past two decades show a broad-based increase in corporate saving across major advanced economies.
- Key empirical relationships and statistics:
  - The corporate saving rate here refers to total gross saving (undistributed gross profits) as a share of gross value added.
  - Among publicly traded firms, the average saving rate across narrowly defined (four-digit NACE) industries in Group of Seven (G7) countries comoves strongly over time with the average share of sales by the largest four firms in an industry, with a correlation coefficient of 0.8.
- Four key findings from analysis of listed firms in the G7:
  - Most of the increase in aggregate corporate saving reflects higher saving by incumbent firms rather than compositional changes driven by entry of new firms, exit, or market share reallocation among incumbent firms.
  - Incumbent firms have been increasing their saving rates more in industries where concentration (or markups) has risen more.
  - Rising pretax profits (gross operating surplus) as a share of corporate value added are the main source for the increase in corporate saving in concentrating industries. Despite rising profitability, firms in industries with larger increases in concentration have not significantly raised their dividends or tax payments.
  - The within-firm rise in saving has been driven by large firms, with the top 1 percent (by size) showing the largest increases.
- Suggested mechanism and open questions:
  - One possible factor is the trend decline in global real interest rates (and corporate tax rates) over the past couple of decades; larger firms being less financially constrained benefit disproportionately from lower interest rates and may save more to finance future high-return projects.
- Empirical approach note:
  - A panel regression is estimated using Worldscope data for 1996–2014:
    - s_ijct = β_0 + β_1 CR4_jt + β_2 X_ijct + γ_ct + δ_i + ε_ijct,
    - where s_ijct = Grosssavings / Grossvalueadded is the saving rate of firm i in industry j, country c, at time t; CR4 is market concentration measured as the fraction of total sales (or assets) accrued to the four largest firms in an industry j; X_ijct is a vector of other firm-specific controls; γ_ct and δ_i are country-year and firm fixed effects. Coefficient β_1 is found to be positive and statistically significant.

### Box 2.2 — Effects of Mergers and Acquisitions on Market Power
- Context: Renewed debate on welfare implications of mergers and acquisitions; mergers may raise efficiency but also can raise prices or reduce variety through consolidation.
- Data: Extensive firm-level markup dataset combined with transaction-specific mergers and acquisitions (M&A) data (Zephyr). Note: deal values are often underreported; main empirical analysis abstracts from deal values.
- Main empirical findings:
  - Mergers and acquisitions are followed by markup increases by acquiring firms.
  - Regression specification explains firm markup by a dummy that switches from 0 (in 2000) to 1 from the year of M&A, controlling for firm and country-industry-year (four-digit NACE) fixed effects, firm size (operating revenue), efficiency (total factor productivity), and profitability (earned income before interest and taxes divided by total assets); standard errors clustered at the firm level.
  - Results show a sizable and statistically significant association between M&A and the subsequent change in a firm’s markup:
    - On the order of 1.1 percentage points, on average (all deals).
    - 1.2 percentage points for horizontal mergers and acquisitions.
  - Counterfactual exercise using announced-but-withdrawn deals (aspiring acquirers) yields a statistically insignificant negative relationship between markups and the post-M&A period for withdrawn deals; sample size is smaller and may be affected by deal-specific reasons for failure.
- Caveats and open issues:
  - More detailed analysis is required to establish a causal link between M&A activity and increasing markups and to assess impacts on productivity and other measures of economic efficiency that benefit consumers.
  - A full welfare assessment requires comparing the efficiency gains (if any) from M&A with the effects on markups and consumer welfare.

*International Monetary Fund | April 2019*

### CHAPTER 2

### CHAPTER 2  ThE RISE OF CORPORaTE MaRKET POWER aND ITS MaCROECONOMIC EFFECTS

### Introduction
- Over the past three decades, the price of machinery and equipment has fallen dramatically relative to other prices in advanced and emerging market and developing economies alike.
- Worldwide, investment growth has slowed considerably since the global financial crisis of 2008–09.
- When compared with its levels in the early 1990s, real investment in machinery and equipment as a share of real GDP has increased significantly.
- The chapter examines whether rising trade tensions, a slowing pace of trade integration, and sluggish productivity growth could threaten the decline in the relative price of capital goods and thereby the investment impetus it has provided.

### Key questions examined
- How have prices of investment goods evolved over time and across countries? Do lower-income countries face higher capital goods prices, in absolute terms and/or relative to other prices in the economy?
- What drives the price of tradable capital goods over time, and which factors explain differences across countries? How much have technological advances and trade integration contributed to the relative decline in the prices of machinery and equipment? To what extent are capital goods prices shaped by policy choices, particularly barriers to trade?
- How responsive is investment in machinery and equipment to the price of these assets? How much have changes in capital goods prices contributed to capital deepening over the past three decades?

### Main findings
- The relative price of tradable investment goods, namely machinery and equipment, has declined across advanced, emerging market, and developing economies over the past three decades. The declines have been significant and have been driven by faster productivity growth in capital goods production and deepening trade integration.
- In 2011, emerging market and developing economies faced higher machinery and equipment prices, both in absolute terms and especially relative to the price of consumption.
- The higher relative prices of machinery and equipment in emerging market and developing economies reflect:
  - lower relative efficiency in producing investment goods and tradable goods more broadly, and
  - significantly higher trade costs, such as those arising from higher tariffs.
- Model simulations and empirical evidence suggest that the relative price of investment goods is an important driver of real investment rates.
- Over the past 30 years, real investment in machinery and equipment as a share of real GDP has increased significantly in both advanced as well as emerging market and developing economies. A nontrivial share of this increase can be attributed to the decline in the relative prices of machinery and equipment.

### Drivers of the decline in relative capital goods prices
- Faster productivity growth in capital-goods-producing sectors relative to consumption sectors, linked in part to advances in information technology.
- Efficiency gains from globalization and the specialization of production, with production of machinery and equipment strongly embedded in global value chains.
- Deepening trade integration enabled many emerging market and developing economies to benefit from cross-border specialization and knowledge transfer.

### Threats to continued declines in capital goods prices
- Slowing global trade, maturation of global value chains, and a waning pace of trade liberalization since the mid-2000s may limit further declines.
- Hikes in tariffs and nontariff barriers could:
  - disrupt cross-border supply chains,
  - make production less efficient,
  - slow or reverse the downward trend in capital goods prices.
- Even economies not directly involved in contemporaneous trade tensions stand to lose if disputes escalate, particularly net importers of capital goods.
- Sluggish productivity growth in advanced economies—exacerbated by the global financial crisis’ lasting effects on research and development and technology adoption, aging, and rising market power—poses another threat.
- The pace of decline in the relative price of machinery and equipment has already slowed considerably in advanced economies in the past decade, potentially adding to their investment weakness since the global financial crisis (see Figure 3.1, panel 6).

### Patterns over time (stylized)
- Since the 1990s, relative prices of the four main types of fixed capital assets—structures, machinery and equipment (excluding transportation), transportation equipment, and intellectual property products—have evolved quite differently.
- The capital deepening in emerging market and developing economies coincided with sizable declines in the price of machinery and equipment relative to the price of consumption.
- Production of machinery and equipment is strongly embedded in global value chains (see Figure 3.1, panel 7).

### Policy implications and recommendations
- Reduce trade costs and reinvigorate international trade:
  - Many emerging market and developing economies maintain trade barriers that raise the relative price of capital goods for domestic investors; removing these barriers would further boost investment in tradable capital goods and support capital deepening.
  - Advanced economies should guard against protectionist measures that raise trade costs; reviving trade liberalization, which has slowed down significantly since the mid-2000s, is vital for maintaining the pace of decline in relative capital goods prices.
- Support continued technological progress and innovation in capital goods production:
  - Policies that stimulate research and development, entrepreneurship, and technology transfer, alongside continued investment in education and public infrastructure, can help sustain declines in relative capital goods prices and generate productivity dividends.
- Recognize the distributive and development implications:
  - Lower relative investment prices have been an important tailwind for investment worldwide and for narrowing income gaps via faster growth in emerging market and developing economies; policy choices that reverse this trend could impede convergence and investment-led growth.

*Source: CHAPTER 2 and accompanying text in the provided content unit, International Monetary Fund | April 2019.*

### 9.0 across 180 countries, the prices of machinery

### The Price of Capital Goods: a Driver of Investment Under Threat?

### Trends in Relative Prices of Capital Goods
- Machinery and equipment and transportation equipment prices have declined significantly since the early 1990s when compared with the consumption deflator (Penn World Table 9.0 across 180 countries).
- The relative price of machinery and equipment fell by about 60 percent in advanced economies and 40 percent in emerging market and developing economies.
- Within machinery and equipment:
  - Computing equipment (computer hardware) prices fell by 90 percent since 1990.
  - Communications equipment prices fell by almost 60 percent.
  - Other investment (mostly intellectual property products such as research and development and computer software and databases) also declined, but more modestly than tangible tradable investment goods.
- The price of residential and nonresidential structures has tracked consumption prices more closely and, in advanced economies, has increased in relative terms since the mid-2000s.
- Evidence suggests advances in information technology have been important in driving down the relative price of investment (see Figure 3.2, panels 5–7).
- Recent data from 10 advanced economies suggest the rate of decline in the relative price of machinery and equipment has slowed since the global financial crisis.

### Breadth and Timing of Declines
- The pace of decline in the relative price of tangible tradable capital goods accelerated significantly in the 1990s, especially for the emerging market and developing economy country group.
- By 2014, compared with the early 1990s:
  - The price of machinery and equipment declined relative to the consumption deflator in all advanced economies.
  - The price declined in 87 percent of emerging market economies.
  - The price declined in 68 percent of low-income developing countries.
- Box 3.1 documents large declines in the cost of installing and operating low-carbon electric generation capacity for some renewable energy sources over the past decade (price of green capital goods).

### Cross-Country Differences in Absolute and Relative Prices (2011 ICP data)
- Absolute price of machinery and equipment in 2011 was inversely related to countries’ development levels: the same basket costs about 8 percent more in the median low-income country than in the median advanced economy.
- Relative to consumption prices, machinery and equipment prices are substantially higher in lower-income countries: the price in the median low-income country is 2.7 times the price in the median advanced economy.
- Figure 3.3 regression lines:
  - Absolute Price: y = –0.025***x + 1.46
  - Relative Price: y = –0.54***x + 7.30
- Online retailer price data for electronics across a sample of 27 advanced and emerging market economies show a similar pattern (Box 3.2).

### Conceptual Framework: Why Relative Prices Matter for Investment
- A decline in the price of capital goods relative to other prices makes investment more attractive versus consumption and, all else equal, leads to higher real investment rates (higher ratio of real investment to real output).
- Investment decisions also depend on:
  - Expectations of economic prospects
  - Availability and cost of finance
  - Quantity of capital already in use relative to desired capital stock
  - Rate of depreciation
  - Agents’ impatience
- The relative price of capital goods is shaped by:
  - Efficiency in producing machinery and equipment versus other sectors (productivity in tradable goods production)
  - For importers: prices charged by international suppliers and wedges between international and domestic prices due to transportation costs, distribution efficiency, import tariffs, customs regulations, time and cost of logistics, and tax policies (accelerated depreciation, investment tax credits, subsidies), and corruption.

### Drivers of Cross-Country Differences: Empirical Findings
- Global production and exports of capital goods are concentrated in a relatively small number of countries; five large exporters analyzed: United States, China, Germany, France, and Japan.
- Despite this concentration, unit values of capital goods exports from these five exporters show little systematic correlation with the per capita income of the importing country (Figure 3.4, panel 3).
- Trade costs exhibit a clear pattern: they are much lower for advanced economies than for emerging market and developing economies.
- Trade-cost components highlighted:
  - Distance to exporters (weighted by partners’ export shares)
  - Liner shipping connectivity (UNCTAD index)
  - Policy-related barriers (Fraser Institute’s Freedom to Trade Internationally index)
  - Tariffs on capital goods
  - Time and cost associated with documentary compliance, border compliance, and domestic transport when importing
- Countries with higher trade costs tend to have higher absolute prices of machinery and equipment in the 2011 ICP data (Figure 3.6, panel 1).

### Structural and Historical Notes
- Emerging market and developing economies import a significant proportion of capital goods; this makes them more sensitive to exporters’ prices and trade/transport/distribution costs.
- Emerging market and developing economies increased their share of global capital goods exports from 5 percent in 1990 to about one-third in 2016; China’s share rose from 1–2 percent in the 1990s to 18 percent in 2017.
- Comparable cross-country data on capital goods prices are scarce; the ICP provides detailed price data roughly every 5–10 years. Methodological improvements in the 2011 ICP round addressed earlier data quality concerns.

### Implications and Questions Raised
- The dramatic and widespread changes in relative prices over three decades, together with large cross-country differences at a point in time, raise key questions:
  - How significant is the relative price of capital goods for countries’ real investment rates?
  - What are the drivers of the relative prices of tradable investment goods?
  - What is required for the downward trend in these prices to continue?
  - What can lower-income countries do to bring down the price of capital goods relative to consumption in their economies?

*Source: International Monetary Fund | April 2019*

### 1. Distance to Machinery

### 1. Distance to Machinery and Equipment Exporters

### Trade costs in 2011 (cross-country associations)
- The absolute price of machinery and equipment in 2011 was higher in countries with larger trade costs.
- Policy-related trade barriers (tariffs, costs and time to import) are stronger predictors of higher relative capital goods prices than natural barriers (distance, connectivity).
- Trade costs and labor productivity in the tradable versus nontradable sector together can explain up to 60 percent of the cross-country variation in the relative price of machinery and equipment, depending on the trade-cost measure used.

### Quantitative effects from cross-sectional regressions and figures
- Figure 3.5 and Figure 3.6 present median and interquartile ranges for trade-cost measures (Distance to M&E exporters; Liner shipping connectivity; Freedom to trade internationally; Tariffs on capital goods; Costs to import; Time to import) and their association with machinery and equipment prices (2011).
- Panel 1 depicts the percent change in the 2011 ICP absolute price of machinery and equipment associated with a one standard deviation increase in alternative measures of trade costs (estimates based on Online Annex Table 3.4.1).
- Panel 2 decomposes cross-country variation in the 2011 ICP price of machinery and equipment relative to consumption into shares explained by relative labor productivity (tradable vs nontradable) and alternative measures of trade costs (based on Online Annex Table 3.4.2).

### Key estimated elasticities and regression results (sectoral producer prices)
- A 1 percent increase in the import ratio (achievable by a 0.7 percentage point cut in tariffs) reduces the sectoral producer price by about 0.5 percent.
- A 1 percent increase in sectoral labor productivity reduces producer prices by about 0.3 percent.
- Policy-induced increases in import penetration have a strong positive effect on labor productivity at the sector level; capital-goods-producing sectors are particularly sensitive to deepening trade integration.

Table 3.1 (selected coefficients and statistics, all values preserved as in source)
- Relative Import Penetration t – 1: OLS (1) = –0.135***; OLS (2) = –0.107***; IV (3) = –0.574***; IV (4) = 1.363***.
- Difference for Capital Goods Sectors: OLS (1) = –0.191**; OLS (2) = 0.033; IV (3) = 1.407**.
- Relative Productivity t – 1: OLS (1) = –0.316***; OLS (2) = –0.314***; IV (3) = –0.328***.
- Relative Import Penetration for Capital Goods Sectors: OLS (1) = –0.298***; OLS (2) = –0.541*; IV (3) = 2.770***.
- Number of Observations = 16,077 (for columns shown).
- R2 (reported columns) = 0.62, 0.62, 0.56, 0.91.
- Note: All regressions include country-year and country-sector fixed effects. Standard errors clustered at the country and sector level are in parentheses. IV = instrumental variable; OLS = ordinary least squares.

### Over time: decline in relative capital goods prices (2000–11)
- Two-step approach:
  1. Estimate elasticity of producer prices to sectoral labor productivity and exposure to international trade (import penetration = imports/domestic value added) using sectoral producer price data across 40 AEs and EMs during 1995–2011 from the World Input-Output Database; use import tariffs as an instrument for import penetration.
  2. Combine elasticities with changes in relative labor productivity and trade exposure of the capital goods sector to allocate the decline in relative prices between 2000 and 2011 to: (1) direct effect of deepening trade integration; (2) effect of trade integration through higher labor productivity; (3) effect of higher labor productivity not due to trade integration; and (4) a residual.
- Deepening trade integration accounts for the bulk of the decline in relative prices of machinery and equipment, both directly and indirectly through higher labor productivity of domestic capital goods producers.
- Productivity gains in capital-goods-producing sectors not directly linked to trade integration are also a significant factor.
- A nontrivial portion of the decline, especially in EMDEs, is attributed to "other factors" such as the downward trend in world interest rates, financial liberalization, and the emergence of China as a key supplier of tradable investment goods.

### Illustrative quantitative counterfactual (footnote 21)
- If low-income countries were to bring capital goods tariffs to the level of those in advanced economies (reducing tariffs by roughly 8 percentage points), the price of investment goods would decline by about 16 percent.
- Of that 16 percent decline, roughly 40 percent would come from the direct trade integration effect and the rest from higher productivity in the capital goods sector due to greater import competition.

### Macroeconomic implications of shocks to the price of capital goods
- Structural model simulations (IMF’s Global Integrated Monetary and Fiscal model) find:
  - Shocks to relative productivity of the investment-goods-producing sector and tariff cuts that permanently lower the price of capital goods imports lead to sizable and long-lasting increases in the real investment rate in a representative emerging market economy.
  - A 1 percent decline in the price of investment relative to consumption leads to a roughly 0.8 percent increase in the ratio of real investment to real GDP in the medium term.
  - For an average emerging market and developing economy with a ratio of real investment to real output of about 22 percent, a 1 percent decline in the relative price of investment would lead to an increase in the investment rate to 22.2 percent.

### Cross-country empirical evidence on investment responses
- Empirical analysis uses over 60 years of data across 180 AEs and EMDEs from the Penn World Table.
- Reduced-form framework relates real investment in machinery and equipment (as a share of real output) to the price of machinery and equipment relative to the price of consumption.
- Estimation controls for global shocks, time-invariant country characteristics, and country-specific time-varying factors (availability and cost of finance, economic prospects, exposure to global markets and commodity prices, quality of institutions and infrastructure).
- Estimation uses five-year averages to smooth cyclical fluctuations and align with medium-term model relationships.
- Estimation results (detailed in Online Annex 3.6) confirm that real investment rates are shaped by the relative price of machinery and equipment, consistent with model-based findings.

*Source: IMF staff calculations; figures, tables, and notes as provided in the source content.*

### CHAPTER 3

CHAPTER 3

### Sectoral Empirical Evidence and Cross-Country Findings
- The analysis uses EU and World KLEMS data covering 18 (mostly advanced) economies over 1971–2015 to construct sector-specific measures of real investment in machinery and equipment and relative prices for 15 broad economic sectors.
- Baseline estimation relates machinery and equipment investment as a share of sectoral real value added to relative prices using five-year averages.
- Estimated elasticities:
  - Cross-country analysis: A 1 percent decline in the relative prices of tradable capital goods is associated with a 0.3–0.5 percent increase in the real investment rate over a five-year period.
  - Sectoral analysis: A 1 percent decline in the relative price of machinery and equipment is associated with a 0.2–0.5 percent increase in the real investment rate in these capital goods.
- Robustness: Findings are robust to alternative specifications, focusing on the post-1990 period, examining emerging market and developing economies only, and using alternative instrumental variable strategies to correct for potential measurement-error bias.
- Sectoral and firm-level evidence (including firm-level data from Colombia after a sizable tariff cut in 2011) corroborates that lower capital goods prices prompted firms to boost investment.

### Table 3.2: Real Investment Rate and the Relative Price of Machinery and Equipment (Selected Results)
- Dependent variable: Log real machinery and equipment investment-to-GDP ratio; regressions averaged over nonoverlapping five-year windows and estimated with instrumental variable regressions (log price instrumented with its lagged value).
- Estimated coefficients on Log Relative Price:
  - Column (1) All: –0.377***
  - Column (2) Post-1990: –0.292*
  - Column (3) EMDEs: –0.491***
  - Column (4) Sectoral (country-period & country-sector FE): –0.326***
  - Column (5) Sectoral (period & country-sector FE): –0.528***
- Standard errors (in parentheses): (0.116), (0.171), (0.161), (0.078), (0.068)
- Number of Observations: 658, 553, 457, 97, 197 (by column)
- Number of Countries: 127, 127, 93, 18, 18 (by column)
- R2: 0.41, 0.36, 0.38, 0.94, 0.93 (by column)
- First Stage F-Statistic: 118.80, 81.81, 64.04, 44.60, 28.80 (by column)
- Notes: Sectoral regressions include country-period and country-sector fixed effects or period and country-sector fixed effects; standard errors clustered at the country level. EMDEs = emerging market and developing economies. Significance markers: ***p < 0.01; **p < 0.05; *p < 0.1.

### Model Simulations, Comparative Evidence, and Magnitudes
- Model simulations (GIMF) and empirical evidence deliver broadly consistent estimates of the elasticity of the real investment-to-real GDP ratio to the relative price of capital goods.
- Between 1990–94 and 2010–14, real investment-to-real GDP ratios in machinery and equipment grew by approximately 60 percent.
- Decomposition (illustrative exercise using cross-country elasticity and post-1990 relative price changes) attributes parts of the change in real investment rates to:
  1. Decline in real investment prices;
  2. Changes in relevant policies;
  3. Other factors (global trends in investment, convergence, growth expectations);
  4. Residual.
- Improvements in policies and falling relative prices together contributed significantly to the rise in real investment in machinery and equipment in both advanced and emerging market and developing economies.

### Drivers of Declining Capital-Goods Prices and Sectoral Dynamics
- The significant decline in the price of machinery and equipment was driven by:
  - Faster productivity growth in the capital-goods-producing sector.
  - Deepening trade integration, which bolstered price competition in domestic markets and improved production efficiency in the investment goods sector.
- The decline in relative capital goods prices reflects efficiency gains from international trade and advances in information and communications technology.

### Low-Carbon Energy Technologies (Box 3.1) — Price and Investment Patterns
- Between 2009 and 2017:
  - Prices fell by 76 percent for solar photovoltaics.
  - Prices fell by 34 percent for onshore wind turbines.
- Renewable energy capacity grew by about 6.5 percent a year between 2000 and 2017.
- In 2017, more was invested in solar photovoltaics than in all other low-carbon sources combined.
- Contrasting trends: Nuclear energy and hydropower costs rose by 21 percent and 9 percent, respectively, between 2009 and 2017.
- Drivers of divergent cost paths:
  - Solar and wind: R&D, standardization, economies of scale, and learning-by-doing produced continuous cost reductions.
  - Nuclear and hydropower: Larger-scale civil engineering characteristics, limited component standardization, construction delays, and stringent environmental and safety concerns limited cost reductions.
- Box authors: Christian Bogmans and Lama Kiyasseh.

### Policy Implications and Recommendations
- Risks: Rising trade tensions, slower trade integration, and potential reversals of liberalization in some advanced economies could weaken the downward pressure on capital goods prices and thereby reduce a key tailwind for machinery and equipment investment.
- Tariff and trade-barrier context:
  - Effective import tariffs on capital goods in 2011: about 4 percent in emerging market economies and 8 percent in low-income developing countries, compared with close to zero in advanced economies.
  - Fully implementing commitments under the World Trade Organization’s Trade Facilitation Agreement could reduce non-tariff barriers by an equivalent of a 15-percentage point tariff cut in less-developed economies (WTO 2015).
- Recommended policy actions:
  - Revive trade liberalization and reduce trade costs from both tariff and other barriers.
  - Address integration-relevant areas such as regulatory cooperation, e-commerce, and complementarities between investment and trade.
  - Encourage research and development, entrepreneurship, and technology transfer to support the capital-goods-producing sector.
  - Continue investment in education and public infrastructure.
  - Design policies to address distributional consequences and job disruptions from technological progress and global integration, including long-term education, lifelong skill-upgrading programs, and policies to facilitate worker reallocation to new jobs.

*International Monetary Fund | April 2019 — CHAPTER 3*

### Box 3.1 (continued)

### Box 3.1 (continued)

### Big-data evidence on cross-country capital-goods prices
- Data and scope:
  - Online price information for 674 distinct Apple products across 27 economies, with a monthly frequency from 2009 to 2012.
  - Prices normalized by US prices and compared for each product within the same month across the 27 economies.
  - Product categories include MacBooks, iPhones, iPods, and cables and accessories; product identifiers specify model, memory, storage, display size, and so on.
  - Online price information from the Billion Prices Project database is identical to the offline price of Apple products, except for shipping cost, local taxes, and store promotions.
  - Although Apple products could be considered consumer goods, they are increasingly used as capital goods—for example, roughly half of all iPads are bought by corporate and government users (Goel 2016).
- Key findings:
  - Significant differences are observed in absolute prices of Apple products across the 27, mostly advanced, economies, with no clear correlation with countries’ per capita income (Figure 3.2.1, panels 1 and 3).
  - Relative to the overall GDP price level, the Billion Prices Project data confirm the regularity established with ICP data: the relative prices of capital goods tend to be significantly lower in richer countries (Figure 3.2.1, panels 2 and 4).

### Model-based analysis of sources of lower investment-goods prices (IMF GIMF simulations)
- Scenarios analyzed (normalized to a 1 percent long-term decline in the relative price of capital):
  - Technology shock: the emerging market becomes permanently more efficient at producing new capital (investment-specific technological change or lower markups in capital-goods sector).
  - Capital goods tariff cut: tariffs on imports of capital goods are permanently lowered.
- Calibration and fiscal implication:
  - Given the model’s assumed share of capital goods imports in overall investment spending (about 33 percent), a 1 percent long-term decline in the relative price of capital requires a 4 percentage point permanent decline in investment goods tariffs in the second scenario, with a recurrent fiscal cost of about 0.25 percent of annual GDP.
- Medium-term (10 years) macroeconomic effects (deviation from original steady state):
  - Investment response: both scenarios raise returns to capital and trigger similar increases in investment.
  - Output:
    - Technology shock: real output increases by 0.7 percent of GDP.
    - Capital goods tariff cut: real output increases by 0.5 percent of GDP.
  - Consumption:
    - Technology shock: household income and consumption increase permanently as the production possibility frontier expands.
    - Capital goods tariff cut: consumption shows little increase because tariff revenue forgone leads to lower public transfers to households and real effective exchange rate (REER) depreciation raises the domestic consumer basket cost; these offset investment-driven demand gains.
  - Real investment, REER, and other variables: both scenarios show declines in the relative price of investment and increases in real investment, with differing magnitudes across variables (see Figure 3.3.1).
- Additional simulation:
  - A decrease in general tariffs equal in fiscal revenue terms to the investment-specific tariff decrease produces no visible effect on the domestic relative price of investment; consequently, the increase in investment is much smaller (0.23 percent versus 1.34 percent in the investment-specific tariff scenario) and the effect on output is smaller (0.18 percent versus 0.5 percent).

### Firm-level evidence from Colombia’s 2011 tariff reform
- Context and reform:
  - Colombian tariff reform aimed to simplify the tariff structure and boost economic growth.
  - Between 2010 and 2011, the average tariff rate on imported goods declined by close to 4 percentage points, from 12.5 percent in 2010 to 8.7 percent in 2011.
- Empirical approach:
  - Event study analysis relating change in firm-level investment rate before and after the tariff reform.
  - Investment defined as investment over total fixed assets for a given firm i.
  - Estimated equation regresses ΔInvestment_i on ΔCapital Input Tariff_s(i), ΔOther Input Tariff_s(i), and ΔOutput Tariff_s(i), where sectoral input tariffs are constructed using 2007 input-output table weights.
- Estimated effects on firm-level investment:
  - A 1 percentage point reduction in capital goods input tariffs is associated with a 0.4 percentage point increase in investment (statistically significant at the 1 percent level).
  - A 1 percentage point reduction in noncapital input tariffs is associated with a 0.15 percentage point increase in investment (statistically significant).
  - Reduction in output tariffs is not associated with significant changes in firms’ investment decisions in the short term.
- Interpretation and robustness:
  - Coefficients on input-tariff changes can be interpreted as effects of price changes on investment rates under the assumption that tariffs are fully passed into importer prices; partial pass-through would attenuate estimates toward zero.
  - Results are robust to standard controls (firm size, sales growth) and to using wider time windows around the tariff cuts.
- Implication:
  - Firms’ investment choices are sensitive to the price of capital goods; cuts in capital goods tariffs have economically and statistically significant effects on firm-level investment.

### Policy implications and synthesis
- Lowering barriers that hamper trade in capital goods and promoting research and development or other measures that improve efficiency in capital-goods sectors are beneficial for output, investment, and consumption in the long term, even if they entail some fiscal costs.
- Investment-specific supply-side improvements (technology, markups) generate larger and more persistent gains in output and consumption than equivalent fiscal-cost tariff cuts that lower imported capital prices without expanding the domestic production possibility frontier.
- Targeted reductions in capital-goods input tariffs can have a substantially larger effect on investment than general tariff reductions.

*International Monetary Fund | April 2019*

### CHAPTER 3

### CHAPTER 3
 ThE PRICE OF CaPITaL GOODS: a DRIvER OF INvESTMENT UNDER ThREaT?

### Key findings and policy conclusions
- Overall trade balances matter more than bilateral trade balances: changes in aggregate trade balances tend to affect most bilateral trade balances, whereas—absent changes in macroeconomic conditions—a change in a bilateral trade balance tends to be offset by changes in bilateral balances with other trading partners, with little or no impact on the overall trade balance.
- The evolution of bilateral trade balances since the mid-1990s was driven largely by macroeconomic factors, specifically the relative movement of aggregate demand and supply in both trading partners and their underlying drivers, including:
  - fundamental factors such as demographics and the level of economic and institutional development;
  - macroeconomic policies, in particular fiscal policy and credit cycles;
  - in some cases, exchange rate policies and domestic supply-side policies (for example, subsidies to production costs).
- Changes in bilateral tariffs played a smaller role in the evolution of bilateral trade balances over the past two decades, reflecting:
  - already-low starting levels of tariffs in many countries;
  - the fact that most countries reduced tariffs at the same time, creating offsetting effects on net trade.
- Tariffs nonetheless matter for bilateral trade costs and, through those costs, for the international division of labor. Declining tariffs:
  - enabled a greater international division of labor, including through global value chains;
  - enhanced competition and access to foreign inputs;
  - contributed to strong productivity improvements, higher output, and employment over the longer term.
- A sharp increase in tariffs would create significant negative spillovers because of the integrated nature of the current trade system; increases in bilateral tariffs will hurt output, employment, and productivity in affected economies and in bystanders up and down value chains. While some countries may benefit from trade diversion, higher tariffs would leave the global economy worse off.
- Two main policy conclusions:
  - Discussion of external balances should focus on macroeconomic determinants of trade and current account balances (for example, fiscal policy), because targeting particular bilateral trade balances will likely only lead to trade diversion and offsetting changes in trade balances with other partners.
  - Multilateral reductions in tariffs and other nontariff barriers will benefit trade and, over the longer term, improve macroeconomic outcomes by allowing countries to specialize according to comparative advantage, integrate into supply chains, and improve access to foreign inputs.

### Introduction and scope
- Public views: in both advanced and emerging market economies, more than 80 percent of the public views trade in a positive light—yet, fewer than half of these people are convinced that trade benefits jobs, wages, or prices; skepticism is particularly pronounced in advanced economies.
- Trade delivers gains (specialization, competition, technology diffusion) but can impose adjustment costs on workers and communities; the consensus of the empirical literature—conditional on appropriate domestic policies—is that open and fair trade with low tariffs and barriers brings lasting net benefits.
- Chapter objectives:
  - What drives bilateral trade balances—role of macroeconomic factors versus tariffs and other micro-structural determinants of comparative advantage and the international division of labor?
  - What is the link between aggregate trade balances (and their drivers) and bilateral balances?
  - What are the consequences when bilateral tariffs are raised, and what spillovers arise for others when accounting for global value chains?

### Analytical approach
- Uses the gravity model for bilateral trade flows to decompose changes in bilateral trade balances into the impact of:
  - trade costs (including tariffs);
  - the international division of labor;
  - macroeconomic factors (aggregate supply and demand).
- Limitations noted:
  - gravity-model variables do not capture all time-invariant determinants of bilateral trade balance levels, so the focus is on explaining changes over time;
  - macroeconomic factors are broad and include demographics, macro policies, and longer-term effects of tariff and supply-side policies that are harder to measure systematically.

### Stylized facts on bilateral versus overall balances and trade integration
- Aggregate and bilateral balances are highly related: for countries with large overall trade imbalances, bilateral trade balances tend to be more one-sided (example countries cited include Germany on the positive side and the United States on the negative side).
- Bilateral trade balances vary widely across partners; even countries with small overall balances can have large, offsetting bilateral balances.
- At the global level, measured in absolute value, global bilateral and overall trade balances evolved broadly in parallel over the past two decades, increasing strongly up to the 2008–09 global financial crisis and dipping during the crisis; bilateral balances increased more than aggregate balances and did not decline as much after the crisis.
- Global trade integration has been fostered by a persistent fall in trade costs:
  - average bilateral trade intensity across country pairs rose between 1995–99 and 2010–15 for most pairs, reflecting lower impediments to trade;
  - transportation improvements reduced shipping costs; expansion of World Trade Organization membership and policy reforms led to generalized declines in import tariffs, particularly where tariffs were initially high (for example, China and other emerging market economies).
- Nevertheless, large variability of bilateral trade intensity remains across country pairs, reflecting bilateral trade costs (tariffs and micro-structural factors) and variation in how macroeconomic factors affect a country’s different bilateral trade balances.

### Economic channels and longer-term effects of tariffs
- Tariffs are an important component of bilateral trade costs that shape the international division of labor.
- Declines in tariffs to lower levels have:
  - allowed greater specialization according to comparative advantage;
  - facilitated participation in global value chains;
  - improved access to foreign inputs and competition, contributing to productivity gains.
- Conversely, increases in bilateral tariffs:
  - protect domestic producers but raise costs for producers up and down supply chains;
  - cause trade diversion and impose negative spillovers on bystanders, amplified through global supply chains;
  - can generate negative confidence effects and tighter global financial conditions that hurt all countries.

### Policy implications for managing adjustment and distributional effects
- While multilateral reductions in tariffs benefit the global economy, valid concerns exist about distributional effects within countries.
- Recommended domestic policies to ensure gains are widely shared and to assist those adversely affected include:
  - enhancing social safety nets (for example, modern income support programs and unemployment assistance programs);
  - retraining and reintegration policies for dislocated workers;
  - tax and benefit policy adjustments to redistribute gains more evenly.

*Source: CHAPTER 3, text - CHAPTER 3 (International Monetary Fund | April 2019)*

### 1. Trade Balance by Partners

### 1. Trade Balance by Partners

### Key empirical findings and figures
- Bilateral trade balances and overall trade balances are presented as percent of global GDP and as sums of absolute values (Figures 4.1–4.2).
- Largest trade flows and organizational "poles" of global production identified for 1995 and 2015: North America (United States with Canada and Mexico), Europe (centered on Germany), and Asia (shift from Japan to China) (Figure 4.5).
- Participation in global value chains (GVCs) is positively correlated with the size of bilateral trade balances (sum of absolute values; percent of GDP); weaker correlation with overall trade balance (absolute values; percent of GDP). Regression fits reported:
  - Bilateral trade balances: y = 0.27x – 7.01, R2 = 0.19
  - Overall trade balances: y = 0.89x – 22.14, R2 = 0.51 (Figure 4.6)
- Data sources: Organisation for Economic Co-operation and Development, Trade in Value Added database; World Bank, World Integrated Trade Solution database; IMF staff calculations.
- Coverage and sample used for estimation: 63 countries; International Standard Industrial Classification of All Economic Activities 3 level; 34 sectors; 1995 to 2015. Data are in nominal US dollars and estimated over five-year periods to remove short-term nominal effects.

### Revealed comparative advantage and sectoral specialization
- Revealed comparative advantage measured by the share of a sector in a country’s exports relative to the sector’s share in world exports (values greater than 1 indicate a revealed comparative advantage) (Figure 4.4).
- Countries that had revealed comparative advantage in manufacturing in 1995 reinforced specialization in manufacturing by 2015: China, Korea, Germany, Japan, and Mexico.
- Relative de-specialization in manufacturing occurred in countries with initial comparative disadvantage: United States and United Kingdom.
- In services, the United Kingdom, India, and the United States built on initial comparative advantage.
- Korea and China developed high-tech manufacturing sectors with strong global trade impact despite modest or absent initial comparative advantage, possibly reflecting relatively higher productivity growth in certain sectors due to innovation.

### Role of global value chains (GVCs) and measurement implications
- Development of global supply chains deepened specialization across and within sectors and amplified multicountry trade patterns. Greater participation in GVCs tends to generate larger bilateral balances (sum of absolute values) but not necessarily larger overall trade balances.
- The difference between gross trade measures and value-added measures has increased because goods sold incorporate value added from various countries along the value chain. Value-added measures are accounted for in subsequent analysis of tariffs’ impact on value added and employment.

### Gravity model: determinants of bilateral trade and elasticities
- The chapter uses the gravity model explaining bilateral exports as a function of:
  - Macroeconomic factors: exporter gross output (aggregate supply), importer gross spending (aggregate demand), scaled by world output. Gross output and spending are used to account for intermediates’ trade in global-value chains.
  - Trade costs: natural and policy-related. The model includes geographic distance; bilateral tariffs; and dummy variables for a common border, a common language, common colonial history, and a common free trade agreement. The model also accounts for exporter and importer average (multilateral) trade costs.
  - Sectoral composition of supply and demand: estimated at the sectoral level and aggregated to country level to capture specialization effects.
- Estimation results: a 1 percent increase in gross ad valorem tariffs reduces gross bilateral exports by about 3–6 percent. The reported range reflects different sector- and country-level estimates.
- Distance is a significant hindrance to both goods and services trade, and is more important for trade in services.
- The gravity model performs well in explaining bilateral exports and imports across specifications but loses explanatory power when directly applied to levels of bilateral trade balances; the chapter therefore focuses on explaining changes in bilateral trade balances rather than levels.

### Decomposition of changes in bilateral trade balances (1995–2015)
- The model is used to decompose changes in bilateral trade balances into contributions from:
  - Macroeconomic factors (country net supply, partner net demand, world output)
  - Sectoral composition (country and partner sectoral composition)
  - Tariffs and other trade costs (bilateral tariffs, country multilateral trade costs, partner multilateral trade costs)
  - Residual (model residuals plus approximation error)
- Average value comparisons use 2010–15 minus 1995–99 averages (Figure 4.7).
- Macroeconomic factors play a prominent role in explaining changes in bilateral trade balances; trade costs also contribute but to a lesser degree.
- The impact of macroeconomic factors on bilateral balances depends on the initial state of bilateral relationships (whether the bilateral balance was large and positive or negative).

### Limitations and caveats
- Results are best interpreted as partial-equilibrium effects; large and persistent tariff changes can influence international division of labor and macroeconomic factors over the longer term (general equilibrium effects), which are further explored in the chapter’s section “A Closer Look at Tariffs and Their Spillovers.”
- Macroeconomic factors capture a broad set of influences (demographics, institutional development, macroeconomic policies, supply-side policies) that are difficult to disentangle with available data.
- Some structural and time-invariant factors determining bilateral balances are imperfectly captured by the gravity model; increasing participation in GVCs may explain rising residuals over time.

*Source: 1. Trade Balance by Partners — text from the IMF World Economic Outlook: Growth Slowdown, Precarious Recovery (April 2019).*

### 1. United States:

### 1. United States:

### Role of macroeconomic factors
- Macroeconomic factors—both domestic and foreign—are, by far, the largest contributors to changes in bilateral trade balances over the period of analysis.
- Domestic macroeconomic conditions reflect the evolution of gross output and gross spending in a particular country; the magnitude of impact depends on the initial bilateral trade balance between the two countries, as determined by trade costs, the international division of labor, initial macroeconomic conditions, and other structural factors.
- Over 1995–2015, US domestic macroeconomic factors had a negative effect on its bilateral trade balances across trading partners because US gross output was growing more slowly than spending: the United States was, in the aggregate, spending more than it was producing, so it had to import more goods from its trading partners.
- Foreign macroeconomic factors are the contributions of the evolution of spending and output in partner countries; the initial structure of trade matters in determining changes in bilateral trade balances.
- Once aggregate and bilateral trade balances are scaled in a theory-consistent way (by taking into account the changing sizes of the trading partners), the shrinking of the aggregate trade balances of the United States and China after the global financial crisis was matched by a corresponding contraction in their bilateral trade balance.

### Role of sectoral specialization
- Changes in the sectoral composition of aggregate demand and supply play a nontrivial role for many bilateral imbalances.
- A positive effect on the bilateral trade balance indicates that the output share of sectors where a country had large initial exports rose (more than the spending share), or that the spending share of sectors where the country had high initial demand fell (more than the output share).
- In the case of the United States, sectoral changes in its supply and demand seem to have contributed positively to its bilateral balances with China, Germany, and Japan.

### Role of trade costs
- Declines in bilateral tariffs contributed to growth in the level of gross trade (exports and imports) but had a more muted impact on trade balances (net trade).
- Tariffs were already low in the mid-1990s in many countries and tariff reductions were often reciprocal, producing offsetting effects on bilateral trade balances.
- Changes in bilateral tariffs contributed slightly positively to changes in US bilateral trade balances with Canada, China, and Mexico because these countries’ tariffs on US goods were falling faster than tariffs imposed by the United States on their goods (albeit from a higher level).
- The estimation suggests that if Chinese tariffs on US goods had remained at their 1995 level, the US–China trade deficit would have been, on average, $30 billion (about 12 percent) larger over 2010–15.
- In many cases, changes in the average trade costs faced by countries across all their trading partners played a larger role than changes in particular bilateral tariffs; rising average trading costs (for example because rapidly growing partners displayed higher tariffs) made trade between lower-cost country pairs more attractive, contributing positively to trade intensity and amplifying bilateral trade balances (for example, widening US bilateral deficits).

### The Role of Macroeconomic Factors (decomposition and policy drivers)
- Any bilateral trade balance depends on:
  - the relative size of the two countries’ aggregate trade balance-to-GDP ratios,
  - the two countries’ sizes relative to the world economy, and
  - bilateral trade intensities.
- Example: a ½ percentage point exogenous decrease in Germany’s overall trade balance—holding everything else constant—would lead Germany’s bilateral trade balances with China, the Netherlands, and the United States to decline by about 0.1 percent of Germany’s GDP, while bilateral trade balances with the United Kingdom and France would decline by 0.05 percent of Germany’s GDP.
- From a policy perspective, the IMF’s External Balance Assessment (EBA) framework links the aggregate trade balance to macroeconomic policies and other drivers; the main EBA determinants fall into four broad groups:
  - Macroeconomic policies: fiscal policy (cyclically adjusted fiscal balance) and exchange rate policy (foreign exchange interventions). Macroeconomic policy distortions (for example, wide-spread export or production subsidies) could also affect macroeconomic imbalances but are difficult to measure systematically and are not explicitly captured here.
  - Credit: captured by detrended private credit to GDP.
  - Cyclical: temporary factors of a cyclical nature, such as the output gap and the commodity terms of trade.
  - Fundamentals: demographics, the level of economic and institutional development, social safety nets, reliance on commodity exports, the country’s net foreign asset position, and the country’s role as a provider of safe and reserve assets.
- Applying the EBA analysis to the United States (and to examples such as Japan, Germany, and China) for average 2010–17 highlights:
  - Financial conditions (credit) have contributed to the reduction in external imbalances: in the United States the contribution of credit conditions to the trade balance is now positive after the correction of the credit boom before the global financial crisis.
  - Fiscal policies matter: the relatively expansionary fiscal stance in the United States after the global financial crisis offset other improvements in the trade balance and, going forward, the recent fiscal stimulus is projected to further widen the trade deficit.
  - Foreign exchange interventions have had only a limited impact on aggregate trade balances and, for China, have largely disappeared in recent years.
  - Cyclical factors provided, on average, a significant negative component in all countries except Japan.
  - Among fundamentals, the level of development is estimated to have made a positive contribution to the aggregate trade balance of advanced economies and a negative contribution for China.
  - Demographic variables make a negative contribution to the trade balance of countries in the late stage of the aging process.
  - The unexplained residual is quantitatively significant and likely reflects macroeconomic distortions not directly accounted for by the EBA drivers, including supply-side policies such as production subsidies and regulatory policies that affect aggregate supply.

### A Closer Look at Tariffs and Their Spillovers
- The direct impact of tariffs on trade balances is small relative to macroeconomic factors.
- Over the longer term, large, sustained changes in tariffs can shape the international division of labor as firms adjust domestic and international investment and production structures, including organization into global value chains.
- The reduction in tariffs and transportation and communications costs since the mid-1990s has coincided with a significant increase in complex global value chain participation (loosely defined as the share of exports that crosses at least two borders).
- Large and persistent increases in bilateral tariffs to prohibitive levels would cripple trade, whether at the bilateral or global level, with severe consequences for the economies involved.

*Source: text - 1. United States: (excerpt from World Economic Outlook: Growth Slowdown, Precarious Recovery, April 2019).*

### 2.5 percent3.0 percent

### The Drivers of Bilateral Trade and the Spillovers from Tariffs

### Measuring tariff spillovers
- Four tariff measures constructed to capture channels of tariff effects in a global value chain (GVC) context:
  - Upstream tariff: the average cumulative tariff applied to the intermediate inputs as a share of the sector’s output (calculated using the global input-output matrix).
  - Domestic protection tariff: the average tariff (import-weighted) imposed on imports that compete with the output of the domestic sector.
  - Downstream tariff: the average cumulative tariff the sector’s output faces when exported either directly or indirectly (calculated using the global input-output matrix).
  - Diversion tariff: the weighted average tariff that partner countries impose on all other suppliers except the country-sector in question.

- Data and scope:
  - Empirical analysis based on a panel data set of 35 countries and 13 manufacturing sectors.
  - There are 92 overall trade deficit reversals referenced in the source material.
  - 2012–15 values are extrapolated based on the Trade in Value Added database (2018).
  - 2011 is the most recent year for the full simulation exercise given data constraints.

### Empirical findings (sectoral panel estimates)
- Main conclusions from the panel analysis controlling for country-specific macroeconomic changes and country-industry characteristics:
  - Tariffs up and down the value chain (upstream and downstream tariffs) matter for output and productivity generally much more than domestic protection tariffs.
  - Upstream and downstream tariffs have statistically significant negative effects on value added, employment, labor productivity, and total factor productivity.
  - Domestic protection tariffs do not appear to have significant effects except for a small negative effect on employment.
  - Evidence of trade diversion: the diversion tariff is positive and statistically significant for value added and employment, but insignificant for labor productivity and total factor productivity.

- Sign and significance pattern (as reported in Table 4.1):
  - Upstream Tariff: negative coefficients for Real Value Added, Number Employees, Labor Productivity, Total Factor Productivity (pattern: – – – –).
  - Domestic Protection: positive for Real Value Added, negative or insignificant for Number Employees and Labor Productivity, positive for Total Factor Productivity (pattern: + – – +).
  - Downstream Tariff: negative coefficients for Real Value Added, Number Employees, Labor Productivity, Total Factor Productivity (pattern: – – – –).
  - Diversion Tariff: positive for Real Value Added, positive for Number Employees, positive for Labor Productivity, negative for Total Factor Productivity (pattern: + + + –).

### Illustrative simulations and spillovers
- Simulations illustrate partial-equilibrium effects of tariff changes (do not include channels such as policy uncertainty, confidence effects, or financial conditions).
- Effect of a generalized 1 percentage point tariff increase by all countries:
  - The negative effect on real value added is larger in 2011 than in 1995 due to increased GVC participation.
  - Countries with large, highly integrated manufacturing sectors (Germany, Korea, China, Japan) face larger overall GDP effects; countries with smaller or less integrated manufacturing sectors (Canada, United States) face smaller effects.

- Effect of a reciprocal 1 percentage point tariff increase limited to trade between China and the United States:
  - China and the United States are the most affected and are both hurt by the move.
  - For China, downstream and, to a slightly lesser extent, upstream tariffs dominate the adverse effect.
  - For the United States, upstream tariffs are more important because intermediate imports from China play a relatively bigger role.
  - Third countries can gain from trade diversion that offsets negative value-chain spillovers; Mexico and Canada benefit most from diversion in simulations of a large US–China dispute.

- General equilibrium simulation of a hypothetical large US–China trade dispute (three modeling approaches):
  - China and the United States suffer the largest losses due to the collapse in bilateral trade and lower returns to capital reflecting tariff distortions.
  - Trade diversion leads to shifts of China’s exports away from the United States toward Mexico, Canada, and east Asia.
  - No economically significant change in either country’s aggregate trade balance despite large bilateral trade declines.
  - Sectoral shifts imply sizable job losses in specific sectors, especially in China and the United States.
  - Overall macroeconomic spillovers in third countries are modest, but sectoral spillovers are larger as GVCs are repositioned.
  - A simulated 25 percent increase in tariffs affecting all US–China trade shows contributions to world real value added that include declines concentrated in Electronics and Other manufacturing, and differential regional impacts (figure-based results in source).

### Impact of greater GVC integration
- Closer integration into GVCs has increased the sensitivity of upstream and downstream tariffs to nominal tariff changes, amplifying their effects.
- The effect of a nominal tariff hike on real value added has become more negative over time (comparison between 1995 and 2011).

### Policy implications and conclusions
- Aggregate imbalances tend to be reflected at the bilateral level; bilateral imbalances are of little consequence for the aggregate unless macroeconomic conditions change.
- Macroeconomic factors (fundamental factors, fiscal policies, credit cycles, exchange rate policies, supply-side policies) played a key role in explaining changes in bilateral balances over the past two decades.
- Two main policy conclusions:
  - Focus on aggregate trade balances and current accounts—and the macroeconomic policies and distortions driving them—rather than attempting to influence specific bilateral trade balances, because attempts to influence a particular bilateral balance are likely to lead to compensating adjustments elsewhere.
  - There is a strong case for lowering tariffs: lower tariffs boost trade and allow the international division of labor to better reflect comparative advantage, leading to output, employment, and productivity gains up and down the value chain.
- Caveats and distributional concerns:
  - While some third countries may benefit from trade diversion, a trade war between China and the United States would also trigger increased uncertainty, negative confidence effects, and tighter global financial conditions, with negative effects on most countries.
  - It is important to have policies in place to ensure that the benefits from trade are widely shared and that the burden of adjustment does not fall on only a few.

*International Monetary Fund | April 2019 — Chapter excerpt on "The Drivers of Bilateral Trade and the Spillovers from Tariffs"*

### 4. United States: Sectoral Trade Balances, 2015

### 4. United States: Sectoral Trade Balances, 2015

### Gross versus Value-Added Trade
- Sectoral trade surpluses and deficits are typically smaller on a value-added than on a gross basis, reflecting the round-trip of production through different sectors.
- For the United States:
  - When measured in value added, the US surplus in services is reduced, and its manufacturing deficit shrinks.
  - Example mechanism: US services (such as intellectual property) used as inputs in the manufacturing sector of other countries lead to manufactured goods that are then imported back to the United States, reducing gross-service surplus and manufacturing deficit on a value-added basis.
- Korea’s surplus with China is smaller in value-added terms because Korea’s gross exports incorporate value added from other countries.
- Aggregate trade balance consistency: when measured against the totality of the rest of the world, a country’s overall trade balance is the same whether measured in gross or in value-added terms.

### Bilateral and Aggregate Trade Balances: Analytical Relationship
- Under the assumption of symmetric trade costs, the gravity relationship can be rearranged to show:
  - The bilateral trade balance between countries i and j (appropriately scaled) depends on the relative evolution of the aggregate trade balance-to-GDP ratio of each country.
  - Appropriate scaling jointly accounts for the output level of both countries; as countries grow, bilateral trade balances tend to increase in absolute value, all else equal.
- The scaled bilateral trade balance formula highlights amplification or dampening by bilateral trade intensity m_ij, which summarizes pair-specific bilateral and multilateral trading costs and micro-structural determinants.
- Application to US–China:
  - When scaled by US GDP only, the US–China bilateral trade imbalance did not shrink after the 2008–09 global financial crisis.
  - When double scaling (including China’s growing share of world GDP) is applied, a notable reduction in the scaled bilateral imbalance emerges, consistent with the decline in global imbalances after the global financial crisis.
  - A predicted series constructed as m_ij times the difference in aggregate trade-balance-to-GDP ratios of the two countries tracks the actual scaled bilateral balance closely, indicating macroeconomic imbalances played a key role in its evolution; imperfections indicate changing trade intensity also matters.

### Do Bilateral Adjustments Drive Overall Trade Deficit Reversals?
- Identification of large trade deficit adjustment episodes follows three criteria:
  1. Average reduction in the overall trade deficit is at least 3 percentage points of GDP over three years relative to the three-year average before the event.
  2. The maximum trade deficit in the three years after the reversal is lower than the minimum deficit in the three years preceding the reversal.
  3. There is no other episode in the following six years.
- Using IMF Direction of Trade Statistics data from 1980–2017 for countries with nominal GDP above the world median in 2017 (excluding fuel exporters), 92 large deficit-adjustment episodes were identified.
  - Of these, only 17 percent (16 out of 92) were associated with large bilateral trade adjustment by at least one of the five biggest deficit partners.
  - A lower bilateral adjustment threshold of 2½ percentage points would increase episodes with large bilateral adjustments from 16 to 22.
- Concentration of absolute adjustments:
  - The five biggest deficit partners are, on average, responsible for 54 percent of deficit correction.
  - The next five are responsible for 12 percent of the correction.
  - The following five explain 8 percent of the correction.
- Relative adjustments (adjusted for initial trade balance) are more evenly distributed:
  - Mean adjustment for the top five deficit partners is about 48 percent of their initial level.
  - Mean adjustment for deficit partners ranked six to ten is about 52 percent of their initial level.
- Regression analysis: all trading partners contribute to trade deficit adjustments; disproportionate reductions with top trading partners are not necessary for overall trade balance reduction.
- Policy implication: targeting bilateral trade balances would likely not help reduce a country’s overall current account deficit; macroeconomic policies (affecting saving and investment) are the appropriate lever.

### The Global Macro and Micro Effects of a US–China Trade Dispute: 25 Percentage-Point Tariff Increase Scenario
- Scenario: hypothetical increase in tariffs on all US–China goods trade by 25 percentage points.
- Models used: GIMF (dynamic stochastic general equilibrium), GTAP (multisector perfect-competition computable general equilibrium), CFRT (multisector heterogenous-firm model à la Melitz).
- Model emphases:
  - GIMF: aggregate effects over time; distinguishes short term (nominal and real rigidities amplify expenditure-switching) and medium/long term (permanent distortions to capital and labor levels).
  - GTAP and CFRT: rich sectoral and regional disaggregation; emphasize inefficient and uneven factor reallocation across sectors; CFRT amplifies reallocation via increasing returns to scale from firm-level fixed costs.
- Calibration note: substitution between any two foreign suppliers is easier than between a foreign supplier and a domestic firm; this tends to amplify positive effects on third countries via diversion to non-China foreign suppliers.

Effects on the United States and China
- US–China trade collapse:
  - Falls by 25–30 percent in the short term (GIMF).
  - Falls somewhere between 30 percent and 70 percent over the long term, depending on model and direction of trade (Table 4.4.1).
- Annual real GDP losses:
  - United States: range from –0.3 percent to –0.6 percent.
  - China: range from –0.5 percent to –1.5 percent.
- Model-specific dynamics:
  - GIMF: effects on China more pronounced in the short term due to insufficient wage and price adjustment; negative effects on the United States grow over the long term as higher tariffs and a more appreciated exchange rate lower returns to capital.
  - CFRT: effects on China amplified by loss of economies of scale.
- Terms of trade:
  - Improve in the United States.
  - Worsen in China.
- Multilateral trade balance: although the US–China bilateral trade deficit is reduced, there is no economically significant change in each country’s multilateral trade balance (GIMF result).

Macro Spillovers to Third Countries
- Robust cross-model result: third countries increase exports to the United States but decrease exports to China.
  - Much of global trade diversion involves third countries increasing exports to the United States at the expense of China while importing more intermediate goods from China.
- Effect on third countries’ overall exports:
  - Generally positive.
  - Mexico and Canada benefit the most due to proximity and strong trade links with the United States.
  - Across models, the increase in third-country exports is most notable in GIMF in the short term and in CFRT; GTAP shows weaker and in some cases negative responses.
- Effects on third-country output:
  - More model variation; typically modest in size.
  - GIMF shows positive short-term effects, including relatively large ones in other North America (excluding the United States), reflecting strong trade diversion amid nominal rigidities.
  - Over the long term, effects are small but negative in every region except other North America (excluding the United States), due to capital-reducing distortions.

Key Quantitative Results (selected, as reported)
- Short-term percentage decrease in US–China trade: 25–30 percent (GIMF).
- Long-term decrease in US–China trade: between 30 percent and 70 percent (model- and direction-dependent).
- Annual real GDP losses:
  - United States: –0.3 percent to –0.6 percent.
  - China: –0.5 percent to –1.5 percent.
- GIMF Year 1 and Long Run impacts on exports to the United States (selected regions, percentage point change from baseline):
  - Asia: 3.7 (Year 1), 1.8 (Long Run)
  - Euro Area: 3.8 (Year 1), 1.7 (Long Run)
  - NAFTA: 2.6 (Year 1), 0.7 (Long Run)
  - Rest of the World: 3.1 (Year 1), 1.7 (Long Run)
- GIMF Year 1 and Long Run impacts on exports to China (selected regions, percentage point change from baseline):
  - United States exports to China: –27.5 (Year 1), –36.4 (Long Run)
  - Asia: 0.5 (Year 1), –1.5 (Long Run)
  - Euro Area: 1.3 (Year 1), –1.6 (Long Run)
  - NAFTA: –0.4 (Year 1), –2.6 (Long Run)
- Table 4.4.1 (selected bilateral export changes, model-specific):
  - China exports to the United States: GIMF Year 1 –20.9; GIMF Long Run –25.1; GTAP –71.3; CFRT –56.0.
  - United States exports to China: GIMF Year 1 –27.5; GIMF Long Run –36.4; GTAP –77.6; CFRT –63.7.
  - Exports to the United States (by country/region, GTAP/CFRT selected values):
    - Japan: GTAP 9.2, CFRT 5.8
    - Korea: GTAP 10.3, CFRT 7.7
    - Vietnam: GTAP 13.9, CFRT 9.7
    - Germany: GTAP 8.6, CFRT 4.9
    - Canada: GTAP 7.5, CFRT 2.5
    - Mexico: GTAP 2.8, CFRT 4.3
  - Exports to China (by country/region, GTAP/CFRT selected values):
    - Japan: GTAP –5.3, CFRT –0.8
    - Korea: GTAP –5.3, CFRT –1.3
    - Vietnam: GTAP –3.4, CFRT –3.4
    - Germany: GTAP –4.4, CFRT –1.4
    - Mexico: GTAP –6.3, CFRT –3.5
- Trade balance effects (GIMF):
  - China: –0.2 (Year 1), –0.3 (Long Run) percent of GDP.
  - United States: –0.2 (Year 1), –0.3 (Long Run) percent of GDP.

*International Monetary Fund | April 2019*

### Box 4.4 (continued)

### Box 4.4 (continued)

### Spillovers to Third Countries
- Two trade models produce different magnitudes of spillovers from higher tariffs:
  - GTAP shows positive but small effects on third countries.
  - CFRT shows a number of countries (Mexico, Canada, Malaysia, Thailand, and Korea) experiencing a relatively large expansion in output and benefiting from economies of scale.
- Aggregate spillovers tend to be moderate, but effects vary substantially across countries and sectors.

### Sectoral Reallocations across Countries
- Manufacturing:
  - Shows a large worldwide contraction overall.
  - Major fallout in the electronics and other manufacturing sectors in China.
  - Manufacturing sectors expand in Mexico, Canada, and in Asian countries.
- Services:
  - Expand in China and contract in the other countries mentioned (Mexico, Canada, Malaysia, Thailand, and Korea).
- Agriculture:
  - The US agricultural sector experiences a sizable contraction.
- Model differences:
  - The magnitude of reallocation is larger in CFRT due to economies of scale.

### Labor Market Impacts (Job Losses)
- Sectoral reallocations imply sizable job losses in specific sectors, compounding macroeconomic adjustment for countries with overall contraction (mainly the United States and China).
- CFRT model example:
  - About 1 percent of the workforce is shed in the US agricultural and transportation equipment sectors.
  - About 5 percent of the workforce is shed in China’s other manufacturing sector.

### Repositioning of Global Value Chains (GVCs)
- Electronics and machinery sector:
  - Accounts for about 20 percent of world imports.
  - In CFRT (where reallocation effects are most pronounced), China would eventually stop being the number one exporter of electronics and machinery to the United States.
  - Other countries in Asia, Canada, and Mexico would replace China as top suppliers to the United States.
- Mexico:
  - The sizable entry of new firms into the electronics sector would lead to large increases in imports of intermediates from everywhere else and especially from China (figure labeled "Mexico’s Imports of Intermediate Inputs for the Electronics and Manufacturing Sectors", Percent of GDP).
  - Figure 4.4.3 (US Imports of Electronics and Machinery before and after Tariffs) shows rank and share changes in total US imports of electronics:
    - China: #1, 22.1% → #4, 11.5%
    - East Asia: #2, 15.6% → #1, 17.7%
    - Mexico: #3, 12.6% → #2, 14.6%
    - Canada: #4, 10.8% → #3, 12.3%

### Key Implications
- Tariff-induced reallocations have asymmetric effects across countries and sectors; aggregate moderation masks large sectoral disruptions.
- Economies of scale in models like CFRT amplify reallocation and labor-market impacts.
- Shifts in the geography of production can increase intermediate-input trade, potentially increasing dependence on former large exporters even as final export shares decline.

*International Monetary Fund. Box 4.4 (continued).*

### 1.3 percent of GDP in 2018). These funds are recorded

### text - 1.3 percent of GDP in 2018). These funds are recorded

### Venezuela: data limitations and projection caveats
- Transfers recorded as revenue amount to 1.3 percent of GDP in 2018; therefore, data and projections for 2018–22 are affected by these transfers.
- Key constraints on projecting the economic outlook:
  - Lack of discussions with the authorities (the last Article IV consultation took place in 2004).
  - Incomplete understanding of the reported data and difficulties interpreting certain reported economic indicators given economic developments.
- Fiscal accounts scope:
  - Include the budgetary central government; social security; FOGADE (insurance deposit institution); and a sample of public enterprises, including Petróleos de Venezuela, S.A. (PDVSA).
  - Data for 2018–24 are IMF staff estimates.
- Effects of hyperinflation and paucity of reported data imply IMF staff’s projected macroeconomic indicators need to be interpreted with caution.
  - Nominal GDP is estimated assuming the GDP deflator rises in line with the IMF staff’s projection of average inflation.
  - Public external debt in relation to GDP is projected using the IMF staff’s estimate of the average exchange rate for the year.
- Wide uncertainty surrounds these projections.
- Venezuela’s consumer prices (CPI) are excluded from all WEO group composites.

### Country classification in the WEO
- The WEO divides the world into two major groups: advanced economies and emerging market and developing economies.
- The classification:
  - Is not based on strict criteria, economic or otherwise, and has evolved over time.
  - Aims to facilitate analysis by organizing data into meaningful groups.
- Examples and counts:
  - The 39 advanced economies are listed in Table B.
  - The group of emerging market and developing economies (155) includes all those that are not classified as advanced economies.
  - Some countries remain outside the country classification and therefore are not included in the analysis (examples given: Cuba and the Democratic People’s Republic of Korea).
- Advanced economies subgrouping:
  - The seven largest in terms of GDP based on market exchange rates—the United States, Japan, Germany, France, Italy, the United Kingdom, and Canada—constitute the subgroup of major advanced economies (often referred to as the Group of Seven (G7)).
  - Members of the euro area are distinguished as a subgroup; composite data for the euro area cover the current members for all years.
- Emerging market and developing economies regional breakdowns:
  - Commonwealth of Independent States (CIS); emerging and developing Asia; emerging and developing Europe; Latin America and the Caribbean (LAC); Middle East, North Africa, Afghanistan, and Pakistan (MENAP); and sub-Saharan Africa (SSA).
- Analytical group criteria:
  - Source of export earnings distinguishes fuel (SITC 3), nonfuel, and nonfuel primary products (SITCs 0, 1, 2, 4, and 68). Economies are categorized into one of these groups if their main source of export earnings exceeded 50 percent of total exports on average between 2013 and 2017.
  - Financial criteria separate net creditor and net debtor economies, heavily indebted poor countries (HIPCs), and low-income developing countries (LIDCs).
    - Economies are categorized as net debtors when their latest net international investment position, where available, was less than zero or their current account balance accumulations from 1972 (or earliest available data) to 2017 were negative.
    - Net debtor economies are further differentiated on the basis of experience with debt servicing.
  - HIPC group: countries that are or have been considered by the IMF and the World Bank for participation in the HIPC Initiative to reduce external debt burdens to a “sustainable” level in a reasonably short period of time.
  - LIDCs: countries with per capita income levels below a certain threshold (set at $2,700 in 2016 as measured by the World Bank’s Atlas method), structural features consistent with limited development and structural transformation, and external financial linkages insufficiently close for them to be widely seen as emerging market economies.

### Selected statistical and tabular highlights
- Table A (classification overview) provides group counts and shares in aggregate GDP (PPP), exports of goods and services, and population for 2018.
- Table B lists the 39 advanced economies and subgroups (major currency areas, major advanced economies, and other advanced economies).
- Table C lists member countries of the European Union (not all of which are classified as advanced economies in the WEO).
- Table D maps emerging market and developing economies by region and main source of export earnings (fuel vs. nonfuel primary products).
- Table E classifies emerging market and developing economies by region, net external position, HIPC status, and LIDC status; notation used:
  - Dot (star) indicates that the country is a net creditor (net debtor).
  - Dot instead of star indicates a country has reached the completion point under HIPC.
- Table F lists economies with exceptional reporting periods; examples include:
  - The Bahamas: Jul/Jun (National Accounts)
  - Barbados: Apr/Mar (National Accounts)
  - Bhutan: Jul/Jun (National Accounts) and Jul/Jun (Government Finance)
  - Egypt: Jul/Jun (National Accounts) and Jul/Jun (Government Finance)
  - India: Apr/Mar (National Accounts) and Apr/Mar (Government Finance)
- Table G provides key data documentation (currency, national accounts, CPI, historical data source, latest actual annual data, base year, system of national accounts in use, use of chain-weighted methodology, government finance historical data source, subsectors coverage, accounting practice, balance of payments historical data source, latest actual annual data, statistics manual in use at source). Examples and exact entries are provided for many countries in the table (selected entries referenced in the source).

### Fiscal policy assumptions used in the WEO
- Short-term fiscal policy assumptions normally based on officially announced budgets, adjusted for differences between national authorities and IMF staff regarding macroeconomic assumptions and projected fiscal outturns.
- When no official budget has been announced, projections incorporate policy measures judged likely to be implemented.
- Medium-term fiscal projections are based on a judgment about the most likely path of policies.
- When IMF staff has insufficient information to assess authorities’ budget intentions and prospects for policy implementation, an unchanged structural primary balance is assumed unless indicated otherwise.
- Specific-country practices and input sources are used in forming projections (examples given in source text for Argentina, Australia, Austria, Belgium).

*International Monetary Fund. April 2019. Excerpts from WORLD ECONOMIC OUTLOOK: GROWTH SLOWDOWN, PRECARIOUS RECOVERY — Statistical Appendix.*

### Annex I of the October 1993 WEO.) Net debt is calculated as

### Annex I of the October 1993 WEO.) Net debt is calculated as

### Fiscal projection assumptions for selected economies
- Net debt is calculated as gross debt minus financial assets corresponding to debt instruments.
- Estimates of the output gap and of the structural balance are subject to significant margins of uncertainty.
- Projections are generally based on the authorities’ fiscal plans, with adjustments for the IMF staff’s assumptions. Country-specific notes:
  - Brazil: Fiscal projections for 2019 take into account the deficit target approved in the budget law.
  - Canada: Projections use the baseline forecasts in the 2018 federal budget and the latest provincial budget updates; IMF staff adjusts for macroeconomic differences and incorporates federal, provincial, and territorial budgetary outturns through the third quarter of 2018.
  - Chile: Projections based on authorities’ budget projections, adjusted to reflect IMF staff’s GDP and copper price projections.
  - China: Fiscal expansion is expected for 2019 as a result of personal income tax reform and other measures to respond to economic slowdown.
  - Denmark: 2018 estimates aligned with official budget numbers; 2019 projections incorporate key features of the medium-term fiscal plan in Convergence Programme 2018.
  - France: Projections for 2018 and beyond based on 2018 budget law measures, multiyear law for 2018–22, and 2019 budget law, adjusted for IMF staff macro and revenue assumptions; historical fiscal data reflect September 2018 revisions.
  - Germany: 2019+ projections based on the 2019 Draft Budgetary Plan, adjusted for IMF staff macro framework and revenue elasticities; gross debt estimate includes portfolios of impaired assets and noncore business transferred to winding-up institutions and other financial sector/EU support operations.
  - Greece: 2018 general government primary balance estimate based on preliminary data up to November 2018 (provided by Ministry of Finance as of February 1, 2019); historical data since 2010 adjusted to align with primary balance definition under enhanced surveillance.
  - India: Historical data based on budgetary execution; projections based on information on authorities’ fiscal plans with IMF staff adjustments. Subnational data are incorporated with a lag of up to one year. IMF and Indian presentations differ on divestment and license auction proceeds, net vs gross recording in minor categories, and some public sector lending.
  - Ireland: Fiscal projections based on Budget 2019.
  - Israel: Historical data based on Government Finance Statistics; the central government deficit is assumed to increase to 3.5 percent of GDP in 2019 and to decline afterward, though not in line with medium-term fiscal targets.
  - Italy: IMF staff estimates/projections informed by government 2019 draft budget; IMF staff assumes automatic VAT hikes for next year will be canceled.
  - Japan: Projections reflect announced fiscal measures, including the consumption tax hike in October 2019 and mitigating measures in the FY2019 budget and tax reform.
  - Mexico: 2018 fiscal projections broadly in line with approved budget; 2019+ assume compliance with Fiscal Responsibility Law rules.
  - Netherlands: 2018–24 projections based on authorities’ Bureau for Economic Policy Analysis budget projections, adjusted for macro assumption differences; historical data revised following June 2014 adoption of ESA 2010.
  - New Zealand: Projections based on fiscal year 2018/19 budget and 2018 HYEFU and IMF staff estimates.
  - Portugal: Current-year projections based on approved budget, adjusted for IMF staff macro forecast; subsequent projections assume unchanged policies.
  - Puerto Rico: Projections based on Puerto Rico Fiscal and Economic Growth Plans (FEGPs) prepared October 2018 and certified by the Oversight Board; IMF projections assume federal aid for rebuilding after Hurricane Maria and assume revenue losses from elimination of certain federal funding and tax incentives; IMF projections differ from FEGPs due to accrual versus cash basis and different macro assumptions.
  - Russia: 2018–21 IMF staff estimates based on authorities’ budget; 2022–24 projections based on new oil price rule with IMF staff adjustments.
  - Saudi Arabia: Baseline projections of non-exported-oil government revenues based on policies announced in the 2019 Budget and Fiscal Balance Program 2019 Update; exported oil revenues based on WEO baseline oil prices and assumption of continued OPEC+ compliance; expenditures start from 2019 budget and Fiscal Balance Program 2019 Update with IMF staff estimates of latest policy/economic changes.
  - Singapore: Fiscal year 2019/20 projections based on budget numbers; rest of projection period assumes unchanged policies.
  - South Africa: Fiscal assumptions based on 2019 Budget Review; nontax revenue excludes transactions in financial assets/liabilities (mainly exchange rate valuation gains, sale of assets).
  - Spain: 2019 projections assume expenditures under 2018 budget extension scenario and already legislated measures (including pension and public wage increases) with IMF staff revenue projections; 2020+ projections are IMF staff projections assuming an unchanged structural primary balance.
  - Sweden: Fiscal projections take authorities’ projections based on 2018 December Budget; cyclical impacts calculated using OECD 2014 elasticity methodology (Price, Dang and Guillemette (2014)) to account for output and employment gaps.
  - Switzerland: Projections assume fiscal policy adjusted as necessary to meet Swiss fiscal rules.
  - Turkey: IMF projections assume a more negative primary and overall balance than in authorities’ New Economic Program 2019–21, reflecting IMF staff’s lower growth forecast and definitional differences (IMF-defined fiscal balance excludes some revenue and expenditure items included in authorities’ headline balance).
  - United Kingdom: Projections based on Spring 2019 Budget, with expenditure at budgeted nominal values and revenue adjusted for IMF staff macro forecasts; IMF staff data exclude public sector banks and effect of transferring assets from Royal Mail Pension Plan to public sector in April 2012.
  - United States: Fiscal projections based on January 2019 Congressional Budget Office baseline, adjusted for IMF staff policy and macro assumptions; projections incorporate Tax Cuts and Jobs Act and Bipartisan Budget Act of 2018, adjust accounting treatment of financial sector support and defined-benefit pension plans, and are converted to a general government basis. Data compiled using SNA 2008 and GFS Manual 2014; most series begin in 2001.

### Monetary policy assumptions and key rates
- Monetary policy assumptions follow established country frameworks; in most cases a nonaccommodative stance over the business cycle is assumed.
- London interbank offered rate on six-month US dollar deposits is assumed to average 3.2 percent in 2019 and 3.8 percent in 2020.
- Rate on three-month euro deposits is assumed to average –0.3 percent in 2019 and –0.2 percent in 2020.
- Interest rate on six-month Japanese yen deposits is assumed to average 0.0 percent in 2019 and 2020.
- Country-specific monetary assumptions:
  - Argentina: Consistent with current framework targeting zero base money growth in seasonally adjusted terms.
  - Australia, Canada, Korea, Mexico: In line with market expectations or with attaining inflation targets.
  - Brazil: Consistent with gradual convergence of inflation toward middle of target range.
  - China: Monetary policy expected to remain on hold.
  - Denmark: Maintain peg to the euro.
  - Euro area: In line with market expectations.
  - Hong Kong SAR: Currency board system assumed to remain intact.
  - India: Consistent with achieving Reserve Bank of India’s inflation target over the medium term.
  - Indonesia: In line with maintaining inflation within central bank targeted band.
  - Japan: In line with market expectations.
  - Russia: Projections assume Central Bank of Russia pausing transition to a neutral stance.
  - Saudi Arabia: Projections based on continuation of exchange rate peg to the US dollar.
  - Singapore: Broad money projected to grow in line with projected nominal GDP growth.
  - South Africa: Monetary policy will remain neutral.
  - Sweden: In line with Riksbank projections.
  - Switzerland: Projections assume no change in the policy rate in 2018–19.
  - Turkey: Assumes no changes to current policy stance.
  - United Kingdom: Short-term interest rate path based on market expectations.
  - United States: IMF staff expects continued gradual normalization of the federal funds target rate.

### Key macro projections and tables (select highlights)
- World output (Table A1, annual percent change):
  - World: 2018 = 3.6, 2019 = 3.3, 2020 = 3.6, 2024 = 3.7.
- The Statistical Appendix contains comprehensive country and group tables, including:
  - Table A1: Summary of World Output (real GDP annual percent change by country/group and projections).
  - Table A2–A4: Real GDP and demand components for Advanced Economies and Emerging Market and Developing Economies.
  - Table A5–A7: Inflation summaries (GDP deflators and consumer prices) for country groups and individual economies.
  - Table A8: Major Advanced Economies: General Government Fiscal Balances and Debt (percent of GDP; gross and net debt series).
  - Table A9: Summary of World Trade Volumes and Prices (annual percent changes and price deflators; oil and nonfuel commodity series).
  - Table A10–A12: Current Account Balances in US$ and percent of GDP for countries, regions, and analytical groups.
  - Table A13: Summary of Financial Account Balances (billions of US$; direct, portfolio, other investment, reserves).
  - Table A14: Summary of Net Lending and Borrowing (percent of GDP; savings and investment).
  - Table A15: Summary of World Medium-Term Baseline Scenario (projections for 2019–24; world real GDP, trade, prices, inflation, interest rates, external debt and debt service).
- Medium-term baseline scenario highlights (Table A15):
  - World Real GDP: 2019 = 3.3, 2020 = 3.6; Emerging Market and Developing Economies: 2019 = 4.5, 2020 = 4.4.
  - Consumer Prices: Advanced Economies 2019 = 1.6 percent; Emerging Market and Developing Economies 2019 = 4.9 percent.
  - Real Six-Month LIBOR (world): 2019 = 1.4 percent (as defined: London interbank on US$ deposits minus percent change in US GDP deflator).
  - World Real Long-Term Interest Rate (GDP-weighted): 2019 = 0.4 percent.

### Policy implications and risk considerations (from Executive Board remarks)
- Global activity has recently lost momentum; global trade slowed sharply and trade tensions weakened business confidence.
- Risks to the outlook are skewed to the downside: reescalation of trade tensions, a no-deal Brexit, sudden shifts in market sentiment and tightening financial conditions, and downside risks in systemic economies.
- Policy guidance:
  - Strong global cooperation is urgent—resolve trade disagreements cooperatively and strengthen the open, rules-based multilateral trading system.
  - Macroeconomic policy: calibrate to support growth where output is below potential and policy space exists; withdraw support carefully where needed; in a deeper downturn, adopt more accommodative policies where feasible.
  - Fiscal policy: balance growth and debt sustainability. In high-debt countries, pursue gradual adjustment if financing risks are large; countries with fiscal space should boost demand where slack exists and raise potential growth where economy is above potential. Use automatic stabilizers and avoid procyclical fiscal stances in protracted slowdowns. Adapt fiscal policy to demographics, technology, and global integration; where budgetary room is limited, rely on recomposition and reprioritization.
  - Monetary policy: welcome more gradual normalization by major central banks; clearly communicate reassessments to avoid excessive market swings.
  - Financial stability: vulnerabilities continue to build (rising corporate debt, sovereign–financial nexus, maturity/liquidity mismatches, house price misalignment, sensitivity of portfolio flows). Deploy prudential tools proactively, expand macroprudential toolkits, and repair public/private balance sheets.
  - Structural reforms: essential to lift potential output, inclusiveness, and resilience—raise productivity, encourage labor force participation, upgrade skills, deregulate product markets and services, and strengthen competition policy to address rising corporate market power.
  - Governance and anti-corruption: improve fiscal institutions, transparency, and governance; enhance international cooperation to combat foreign bribery, money laundering, tax evasion.
  - Emerging market and developing economies: focus monetary policy on anchoring inflation expectations where inflation is high and support domestic activity where expectations are anchored; raise revenue, reduce debt vulnerabilities, and progress on economic and financial rebalancing.
  - Low-income developing countries: adopt policies to drive growth, increase resilience to volatile external conditions, reduce debt vulnerabilities, and advance toward the 2030 Sustainable Development Goals—priorities include improving macro frameworks, domestic resource mobilization, fiscal policy geared to growth/development with protection for social spending and select capital projects, and diversification for commodity exporters.

*Italicized source: IMF, World Economic Outlook: Growth Slowdown, Precarious Recovery — Statistical Appendix and Box A1 (April 2019).*

---


_Source: https://www.imf.org/-/media/files/publications/weo/2019/april/english/text.pdf_