## World Economic Outlook: Gaining Momentum? (April 2017) — Selected content unit

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### Assumptions and Baseline Projections (Preface; Projections and baseline assumptions)
- Real effective exchange rates assumed constant at their average levels during February 1 to March 1, 2017 (except ERM II currencies constant in nominal terms relative to the euro).
- Established policies of national authorities are assumed to be maintained.
- Average price of oil assumed to be $55.23 a barrel in 2017 and $55.06 a barrel in 2018 and to remain unchanged in real terms over the medium term.
- Six-month LIBOR on U.S. dollar deposits assumed to average 1.7 percent in 2017 and 2.8 percent in 2018.
- Three-month euro deposit rate assumed to average –0.3 percent in 2017 and –0.2 percent in 2018.
- Six-month Japanese yen deposit rate assumed to yield on average 0.0 percent in 2017 and 2018.
- Estimates and projections are based on statistical information available through April 3, 2017.
- World growth projections:
  - 2016: 3.1 percent (baseline)
  - 2017: 3.5 percent (projection; upward revision of 0.1 percentage point relative to October 2016)
  - 2018: 3.6 percent (projection)
  - Medium term: projected to reach 3.8 percent by 2022
- Oil/fuel price baseline:
  - IMF’s average petroleum spot price: $55.2 a barrel in 2017; $55.1 a barrel in 2018 (futures-based baseline)
  - 2016 average oil price: $43 a barrel (comparison)

### Executive summary — Key findings, risks, and policy priorities
- Global outlook and composition:
  - World growth rising from 3.1 percent in 2016 to 3.5 percent in 2017 and 3.6 percent in 2018.
  - Emerging market and developing economies: pickup in 2017–18 (2016: 4.1 percent; 2017: 4.5 percent; 2018: 4.8 percent).
  - Advanced economies: growth in 2017 and 2018 projected at 2.0 percent in each year.
  - China: 2017: 6.6 percent; 2018: 6.2 percent.
  - United States: 2017: 2.3 percent; 2018: 2.5 percent; potential growth estimated at 1.8 percent.
- Recent developments and indicators:
  - IMF’s Primary Commodities Price Index increased by 15 percent between August 2016 and February 2017.
  - Oil prices increased by some 20 percent between August 2016 and February 2017.
  - Global trade showing signs of recovery; production of consumer durables and capital goods rebounded in late 2016.
- Risks (skewed to the downside, especially over the medium term):
  - Inward shift in policies including protectionism; potential for trade warfare.
  - Faster-than-expected U.S. interest rate hikes and dollar appreciation.
  - Aggressive rollback of financial regulation increasing crisis risk.
  - Financial tightening in emerging markets, vulnerabilities in China’s financial system.
  - Adverse feedback loops among weak demand, low inflation, weak balance sheets, and anemic productivity growth.
  - Noneconomic shocks: geopolitical tensions, domestic political discord, extreme weather, terrorism.
- Policy priorities:
  - Differentiate macroeconomic demand management by cyclical position:
    - Economies with slack and persistently weak core inflation: cyclical demand support.
    - Economies close to or above potential: fiscal policy to strengthen safety nets and increase potential output.
  - Domestic reforms to boost productivity and share gains:
    - Active labor market policies.
    - Greater tax progressivity where helpful.
    - More effective investment in education.
    - Changes to housing and credit markets to facilitate worker mobility.
  - Combine monetary, fiscal, structural, and financial sector policies to strengthen recovery.
  - Preserve open trading system and multilateral cooperation; avoid protectionist measures.

### Advanced economies — Recent dynamics and outlook (Chapter 1; Advanced Economies)
- Activity and inflation:
  - Global economic activity gained momentum in Q4 2016; inventories began contributing positively to U.S. growth after five quarters of drag.
  - In advanced economies, 12-month consumer price inflation in February 2017 stood slightly above 2 percent (more than double the average annual inflation rate of 0.8 percent in 2016).
  - Core inflation remains subdued and below central bank targets in almost all advanced economies.
- Financial markets and rates:
  - Nominal yields on 10-year U.S. Treasury bonds increased by some 85 basis points compared with August 2016 and 55 basis points compared with just before the U.S. election (as of end-March 2017).
  - Italian yields rose about 120 basis points after August; German yields rose about 40 basis points.
  - U.S. Federal Reserve raised short-term interest rates in December 2016 and March 2017; markets priced in two additional rate increases by end-2017 or early-2018.
  - U.S. dollar strengthened in real effective terms by about 3.5 percent between August 2016 and late March 2017.
- Constraints and medium-term headwinds:
  - Demographic headwinds and weak trend productivity likely to restrain medium-term growth.
  - Recovery remains ongoing but output remains below potential in many advanced economies; unemployment above 2008 levels in many countries.

### Real policy rates, fiscal and monetary policy assumptions (2. Real Policy Rates; 2. Change in the Structural Fiscal Balance)
- Fiscal policy:
  - Global fiscal stance projected broadly neutral in 2017 and 2018, masking diversity across countries.
  - Advanced-economy fiscal stance in 2017 (fiscal impulse):
    - Expansionary in Canada, France, and Germany.
    - Contractionary in Australia, Korea, and the United Kingdom.
    - Broadly neutral in Japan and the United States.
  - U.S. fiscal deficit assumed to widen by 2 percentage points of GDP by 2019 (fiscal impulse of 1 percent of GDP), with about equally sized decreases in personal and corporate income tax burdens concentrated in 2018 and 2019.
- Monetary policy:
  - Forecast assumes less gradual normalization of policy interest rates in advanced economies, particularly the United Kingdom and the United States.
  - U.S. policy interest rate projected to rise by 75 basis points in 2017 and 125 basis points in 2018, reaching a long-term equilibrium rate of just below 3 percent in 2019.
  - In other advanced economies, short-term rates projected to remain negative in the euro area through 2018 and close to zero in Japan over the forecast horizon.
- Global fiscal projections and key numbers:
  - World growth: 2016 = 3.1 percent; 2017 = 3.5 percent; 2018 = 3.6 percent.
  - Advanced economies group growth in 2017 and 2018: 2.0 percent in each year (0.2 percentage point higher than October 2016 expectations).
  - Emerging market and developing economies: 2016 = 4.1 percent; 2017 = 4.5 percent; 2018 = 4.8 percent.
  - Medium-term: EMDEs projected to increase to 5 percent by end of forecast period.

### Scenario Box 1 — Permanent U.S. Fiscal Expansions (G20MOD simulations)
- Two illustrative debt-financed fiscal expansions (2018–21) with identical instruments: reduced labor income taxes, reduced corporate income taxes, and increased infrastructure spending.
- Common assumptions:
  - Debt financed for first four years (2018–21); monetary policy responds endogenously; monetary policy in Japan and euro area accommodates positive demand increases.
  - After four years (2022) fiscal authority adjusts policy to stabilize debt-to-GDP roughly 5 percentage points above prestimulus level.
- Highly productive expansion (assumptions/results):
  - Productive infrastructure spending; broad-based labor income tax cuts.
  - U.S. Real GDP peaks at 1 percent above the no-policy-change case in 2021.
  - Other advanced economies: GDP roughly 0.2 percent higher in the short term.
  - Long-term: permanently higher U.S. output if public capital raises private productivity.
- Less productive expansion (assumptions/results):
  - Infrastructure spending assumed unproductive; tax cuts skewed to wealthy (low marginal propensity to spend).
  - Faster normalization of term premia (25 basis points in 2018 and additional 25 basis points in 2019).
  - U.S. Real GDP rises roughly half as much by 2021 compared with highly productive case.
  - Short-term spillovers negative for other advanced and emerging market economies due to tighter global financial conditions.
- Scenario Table 1 — The Impact of Fiscal Measures on the Deficit (percent of no-change-in-fiscal-measures case GDP)
  - Highly Productive Fiscal Measures (2017–2022 entries):
    - Capital Income Taxes: 0 0.375 0.750 0.750 0.750 0.750
    - General Labor Income Taxes: 0 0.375 0.750 0.750 0.750 −0.330
    - Productive Infrastructure Spending: 0 0.250 0.500 0.500 0.500 0.150
    - Tax, Expenditures: 0 0 0 0 0 −0.320
    - Total Change in the Deficit: 0 1.000 2.000 2.000 2.000 0.200
  - Less Productive Fiscal Measures (2017–2022 entries):
    - Capital Income Taxes: 0 0.375 0.750 0.750 0.750 0.750
    - Labor Income Taxes for the Wealthy: 0 0.375 0.750 0.750 0.750 0
    - General Labor Income Taxes: 0 0 0 0 0 −0.530
    - Unproductive Infrastructure Spending: 0 0.250 0.500 0.500 0.500 0
    - Total Change in the Deficit: 0 1.000 2.000 2.000 2.000 0.220

### External environment and implications for Emerging Market and Developing Economies (Chapter 2 — Roads Less Traveled)
- Research focus:
  - Role of country-specific external demand, external financial conditions, and terms of trade in medium-term growth (five-year horizons) and in driving accelerations and reversals.
- Measurement constructs:
  - External demand: export-weighted growth rate of domestic absorption of trading partners (decomposed by China, other EMDEs excluding China, and advanced economies).
  - External financial conditions: quantity-based measure of capital flows to peer economies as a share of their aggregate GDP.
  - Commodity terms of trade (CTOT): international commodity prices weighted by net export shares in GDP.
- Main estimated elasticities (1970–2014; statistically significant at 10 percent level in full sample):
  - A 1 percentage point increase in trading-partner domestic absorption growth → ~0.4 percentage point increase in medium-term growth.
  - A 1 percentage point of GDP increase in regional capital flows → ~0.2 percentage point rise in medium-term growth.
  - A 1 percentage point increase in commodity terms of trade → almost 0.5 percentage point increase in medium-term growth.
- Evolution over time:
  - Contribution of country-specific external conditions to per capita growth increased by about ½ percentage point between 1995–2004 and 2005–14 (about one-third of the increase in average per capita income growth).
  - Financial conditions’ contribution rose and accounts for about half of external factors’ contribution since 2005 (up from about one-third in 1995–2004).
  - China and other EMDEs together account for more than 80 percent of external demand contribution to other EMDE growth (up from 36 percent in late 1990s).
- Episodes (1970–2014):
  - Persistent accelerations: 95 episodes (of 127 total accelerations).
  - Reversals: 125 episodes.
  - Median annual growth during persistent accelerations: about 5.5 percent; comparators: 1.7 percent.
  - Persistent accelerations: cumulative increases in income per capita typically 15–40 percent above starting level.
  - Reversals: typical cumulative declines 5–30 percent (extremes up to 50 percent).
- Marginal effects (logit regressions; external conditions at means):
  - Persistent accelerations:
    - 1 percentage point increase in trading-partner demand → raises probability of acceleration by 3.9 percentage points (increases unconditional probability to 9.7 percent).
    - 1 percentage point of GDP increase in regional capital flows → raises probability by 2.6 percentage points.
    - Terms of trade not significant for full sample; significant for commodity exporters.
  - Reversals:
    - 1 percentage point increase in external demand → lowers probability of reversal by 4 percentage points.
    - 1 percentage point of GDP increase in regional capital flows → associated with a 2.4 percentage point decrease in reversal probability.
    - Change in terms of trade associated with 0.6 percentage point reduction in reversal likelihood.
- Domestic attributes that mediate external impacts (key quantitative statements preserved):
  - Raising number of free trade agreement partners from 25th to 75th percentile: a 1 percentage point increase in external demand raises acceleration probability by 3 additional percentage points.
  - Financial development amplification: 1 percentage point of GDP increase in capital inflows raises acceleration probability by 6.6 percent at 75th percentile of financial development vs 4.5 percent at 25th percentile.
  - Sound monetary frameworks, financial depth, exchange rate flexibility, stronger institutions (legal/property rights) increase chance of accelerations and reduce chance of reversals.
  - Lower external debt and small current account deficits improve marginal effects of better external conditions on accelerating growth.
- Policy recommendations for EMDEs:
  - Protect trade integration and permit exchange rate flexibility.
  - Strengthen institutional frameworks, deepen financial systems, contain vulnerabilities from high external imbalances and public debt.
  - Use macroprudential tools and improve governance to better capture benefits of external conditions.

### Commodity market and oil (Special Feature; 3. Brent Price Prospects; The Role of Technology and Unconventional Sources)
- Oil market developments:
  - OPEC and non-OPEC cuts: additional cuts about 0.6 mbd; Russia committed 0.3 mbd; total reductions including others about 1.8 mbd for six months (effective Jan 2017).
  - OPEC agreed to reduce crude oil output to 32.5 million barrels a day (mbd) effective January 2017 for six months, extendable for another six months (implies ~1.2 mbd cut from October 2016).
  - Spot oil prices moved to more than $50 a barrel after agreements.
  - IEA January 2017: only a few OPEC members fully complied; Saudi Arabia cut more than initially agreed; Libya increased production (exempt).
- Baseline oil price assumptions:
  - IMF baseline: average petroleum spot prices of $55.2 a barrel in 2017 and $55.1 a barrel in 2018.
- Unconventional oil and technology:
  - Shale/tight oil: light crude in low-permeability formations; lower sunk costs; short lag from investment to production.
  - Shale added 7.9 mbd in a 96 mbd market in 2016: 4.4 mbd crude oil, 2.7 mbd natural gas liquids, 0.8 mbd condensate.
  - Shale supply response can moderate price spikes; rapid U.S. shale recovery could tip market back into surplus in H2 2017.
- Other commodities since August 2016 (percent changes preserved):
  - IMF’s Primary Commodities Price Index increased by 15.5 percent since August 2016.
  - Energy rallied by 21.1 percent; metals rallied by 23.6 percent; food prices rose by 4.9 percent; oil prices up by 21.2 percent; coal rallied by 21.0 percent.
  - Metal prices expected to stay near current levels; iron ore expected to decline sharply.
- Agricultural projections:
  - Annual food price projections: increase by 3.0 percent in 2017, drop by 0.5 percent in 2018, broadly unchanged thereafter.
- Capital expenditure and breakeven notes:
  - Total world production in 2016 estimated at 96.5 mbd.
  - Breakeven price markers in Figure 1.SF.6 include: 29, 43, 49, 53, 54, 55, 57, 62, 74 (U.S. dollars a barrel).

### Labor income shares — Trends, drivers, and policy implications (Chapter 3 — Understanding the Downward Trend in Labor Income Shares)
- Stylized facts and scope:
  - Between 1991 and 2014, labor share declined in 29 of the largest 50 economies (those 29 accounted for ~two-thirds of world GDP in 2014).
  - Across industries, labor shares declined in 7 of 10 major industries; sharpest declines in tradable sectors (manufacturing; transportation and communication).
  - Shift-share decomposition (1993–2014): over 90 percent of changes in labor shares reflect within-industry changes rather than reallocation across industries (exception: China where reallocation from agriculture accounts for majority of decline).
- Main identified drivers and quantitative roles:
  - Advanced economies:
    - Technological progress (steep decline in relative price of investment goods) combined with initial exposure to routinization explains about half of the overall decline in labor share.
    - For a 15 percent decline in relative price of investment (sample average), country with low initial routinization → 0.4 percentage point decline in labor share; with high routinization → about 1.5 percentage point decline.
  - Emerging market and developing economies:
    - Global integration (participation in global value chains) is a dominant driver of labor share evolution in aggregate; technology plays a smaller aggregate role because relative price of investment declined less (about 7 percent vs about 12 percent in AEs).
    - Financial integration in EMDEs has partly offset declines by raising labor shares in some cases (access to capital lowers user cost).
- Routinization and elasticity of substitution:
  - Elasticity of substitution between capital and labor (ρ) is central: a fall in relative cost of capital r/w lowers labor share iff ρ > 1.
  - Cross-country evidence suggests higher aggregate elasticity in advanced economies (ρ > 1) and lower in EMDEs (ρ < 1) consistent with routinization exposure differences.
  - Initial exposure to routinization (measured 1990–1995) matters: economies with higher initial exposure experienced larger subsequent declines in labor share for a given investment-price shock.
- Skill- and sectoral effects:
  - Middle-skilled labor has borne largest declines in income share; low- and middle-skilled combined labor income share fell by more than 7 percentage points during 1995–2009 while high-skilled labor share rose by more than 5 percentage points.
  - Within-sector changes dominate over between-sector reallocation in driving labor share declines.
  - GVC participation associated with rising capital intensity, particularly in EMDEs.
- Measurement issues and robustness:
  - Self-employment adjustment and depreciation adjustments materially affect levels and trends:
    - Adjusting for self-employment generally makes the labor share decline steeper (especially in EMDEs).
    - Adjusting for depreciation tends to flatten the decline (especially in AEs where ICT capital depreciates faster).
  - Chapter findings robust to adjustments for self-employment and depreciation (Annex and robustness tables).
- Empirical magnitudes and model fit:
  - Aggregate cross-country regression (49 countries) explains about two-thirds of evolution in labor share trends (R-squared examples preserved in Annex: joint specification R-squared = 0.636 in one column).
  - Key joint-specification coefficients (Annex Table 3.5.1, column 6):
    - Relative PI * Initial Routinization: 0.524*** (0.124)
    - Relative PI: 0.183** (0.0734)
    - Financial Integration: 1.72* (0.895)
    - Global Value Chain Participation: −0.574*** (0.0962)
- Policy implications and recommendations:
  - Advanced economies:
    - Policies to help workers adjust to technological change: skill upgrading; lifelong learning; active labor market policies; facilitate reallocation (housing and credit reforms); strengthen safety nets; target distributional measures (progressive taxation and transfers).
    - Complement structural reforms with demand support where slack persists; maintain accommodative monetary policy when appropriate; combine with balance-sheet repair.
  - Emerging market and developing economies:
    - Promote skill deepening to prepare workers for structural transformation.
    - Protect trade integration and permit exchange rate flexibility; ensure financial systems channel capital productively while containing excessive credit growth.
    - Improve institutions, governance, and policies to widen access to gains from growth.
  - Multilateral and longer-term:
    - Preserve open trading system; multilateral cooperation on taxation, financial stability, climate, and support for low-income countries to achieve Sustainable Development Goals.
  - No single policy prescription: responses should be country-specific, accounting for development stage, drivers of labor share decline, and policy space.

### Additional country and data notes (selected items from Statistical Appendix and Annexes)
- Statistical conventions:
  - “Billion” = thousand million; “trillion” = thousand billion.
  - “Basis points” = hundredths of 1 percentage point.
  - Data refer to calendar years except where countries use fiscal years (see Table F).
  - Composite country-group data represent calculations based on 90 percent or more of the weighted group data unless noted.
- Notable data revisions and measurement examples:
  - Ireland 2015 national accounts revisions: GDP growth for 2015 revised from preliminary 7.8 percent to 26.3 percent; GNI growth revised from 5.7 percent to 18.7 percent; acquisition of foreign-owned intellectual property assets added about €300 billion to Ireland’s capital stock and similar amount to net external liabilities.

*Source: World Economic Outlook: Gaining Momentum? — Preface, Executive Summary, Chapters 1–3, Scenario Box 1, Special Features, Annexes and Statistical Appendix (International Monetary Fund, April 2017).*

### Preface                                                                                                                 

### Preface

### Scope and placement
- Preface appears on page xii of the World Economic Outlook: Gaining Momentum? (April 2017).
- The Preface introduces a report whose main structure includes: an Executive Summary; Chapter 1 (Global Prospects and Policies); Chapter 2 (Roads Less Traveled: Growth in Emerging Market and Developing Economies in a Complicated External Environment); Chapter 3 (Understanding the Downward Trend in Labor Income Shares); a Statistical Appendix; World Economic Outlook, Selected Topics; and IMF Executive Board Discussion of the Outlook, April 2017.

### High-level chapter map (as presented in the table of contents)
- Executive Summary: xv
- Chapter 1. Global Prospects and Policies: 1
  - Recent Developments and Prospects: 1
  - The Forecast: 13
  - Risks: 22
  - Policy Priorities: 29
  - Scenario Box 1. Permanent U.S. Fiscal Expansions: 37
  - Box 1.1. Conflict, Growth, and Migration: 40
  - Box 1.2. Tackling Measurement Challenges of Irish Economic Activity: 43
  - Special Feature: Commodity Market Developments and Forecasts, with a Focus on the Role of Technology and Unconventional Sources in the Global Oil Market: 52
  - References: 63
- Chapter 2. Roads Less Traveled: Growth in Emerging Market and Developing Economies in a Complicated External Environment: 65
  - Introduction: 65
  - Emerging Market and Developing Economy Growth Performance over Time: 67
  - How Important Are External Conditions?: 69
  - How Do External Conditions Influence the Occurrence of Growth Episodes?: 76
  - The Role of Policies and Structural Attributes in Mediating the Impact of External Conditions: 82
  - Taking Stock: What Does the Current Environment Imply for Growth Prospects in Emerging Market and Developing Economies?: 87
  - Conclusion: 88
  - Boxes and Annexes: Box 2.1 through Annex 2.6 (pages 89–113, with data and methodology annexes through page 118)
- Chapter 3. Understanding the Downward Trend in Labor Income Shares: 121
  - Introduction: 121
  - Trends in the Labor Share of Income: Key Facts: 126
  - Drivers of the Labor Share of Income: Key Concepts and Mechanisms: 127
  - Analyzing Trends in the Labor Share of Income: Empirical Analysis: 133
  - Summary and Policy Implications: 140
  - Boxes and Annexes: Box 3.1 through Annex 3.5 (pages 142–162, with references through page 170)
- Statistical Appendix: 173
  - Assumptions: 173
  - What’s New: 174
  - Data and Conventions: 174
  - Country Notes: 175
  - Classification of Countries: 175–183
  - Box A1. Economic Policy Assumptions Underlying the Projections for Selected Economies: 193
- Tables and Figures
  - Key tables and scenario tables listed (e.g., Table 1.1. Overview of the World Economic Outlook Projections: 2; Scenario Table 1. The Impact of Fiscal Measures on the Deficit: 38)
  - Extensive lists of annex tables, online tables (Table B1–B21), and figures (Figure 1.1–Figure 3.4.4 and numerous annex figures), covering global activity indicators, commodity and oil markets, fiscal indicators, detailed country and regional breakdowns, growth episode analyses, labor share decompositions, and robustness checks.
- World Economic Outlook, Selected Topics: 229
- IMF Executive Board Discussion of the Outlook, April 2017: 237

### Notable structural and methodological elements highlighted in the table of contents
- Multiple scenario and special-feature analyses, including:
  - Scenario Box 1. Permanent U.S. Fiscal Expansions (Chapter 1, page 37).
  - Special Feature on commodity market developments and unconventional oil (Chapter 1 Special Feature, page 52), with related figures and tables (e.g., Table 1.SF.1. Unconventional Oil Production, 2016: 57).
- Extensive annexes and robustness checks supporting empirical chapters:
  - Chapter 2 includes Annexes on data, channels, estimation, identification of growth episodes, and policy influence (Annex 2.1–2.6, pages 100–118).
  - Chapter 3 includes Annexes on wages and deflators, theoretical models, country coverage and data, methodology, and robustness checks (Annex 3.1–3.5, pages 155–162).
- Statistical Appendix provides assumptions, classification schemes, and comprehensive tables for cross-country projections and indicators (Tables A.1–A.15 and numerous annex tables).

*Source: Preface, World Economic Outlook: Gaining Momentum?, International Monetary Fund, April 2017.*

### Annex Figure 3.4.2. Heterogeneity in the Evolution of Key Drivers of the Labor Share 162

### Annex Figure 3.4.2. Heterogeneity in the Evolution of Key Drivers of the Labor Share 162

### Projections and baseline assumptions used in the WEO
- Real effective exchange rates assumed constant at their average levels during February 1 to March 1, 2017, except for currencies participating in ERM II, which are assumed to have remained constant in nominal terms relative to the euro.
- Established policies of national authorities are assumed to be maintained.
- Average price of oil assumed to be $55.23 a barrel in 2017 and $55.06 a barrel in 2018 and to remain unchanged in real terms over the medium term.
- Six-month LIBOR on U.S. dollar deposits assumed to average 1.7 percent in 2017 and 2.8 percent in 2018.
- Three-month euro deposit rate assumed to average –0.3 percent in 2017 and –0.2 percent in 2018.
- Six-month Japanese yen deposit rate assumed to yield on average 0.0 percent in 2017 and 2018.
- Estimates and projections are based on statistical information available through April 3, 2017.

### Key global growth findings and risks
- Global growth projection for 2017 raised to 3.5 percent, up from the recently forecast 3.4 percent.
- 2018 global growth forecast held steady at 3.6 percent.
- Growth improvements in 2017 and 2018 are broadly based, but growth remains tepid in many advanced economies, and commodity exporters continue to struggle.
- Downside risks to the medium-term outlook are significant and may have intensified since the last forecast.
- A salient threat identified is a turn toward protectionism, potentially leading to trade warfare.

### Analysis linking technology, trade, and labor’s share
- Chapter 3 explores how technology and trade have tended to lower labor’s share of national income in many countries.
- A decline in labor’s GDP share can reflect benign forces (for example, fast productivity growth that benefits capital even more than labor) but is concerning where it coincides with stagnant median incomes and worsening income distribution, as observed in a number of advanced economies.
- Such distributional outcomes can generate political pressures to roll back economic integration with trading partners.

### Policy recommendations to address distributional effects and support productivity
- Follow trade policies consistent with maximum productivity rather than protectionism.
- Supplement openness with domestic policies to better distribute gains from trade and ease adjustment:
  - Active labor market policies.
  - Greater tax progressivity where helpful.
  - More effective investment in education.
  - Changes to housing and credit markets that facilitate worker mobility.
- These domestic reforms both ease economic adjustment and raise potential output over the longer term.
- Monetary, fiscal, structural, and financial sector policies should be combined to strengthen and secure the recovery over time.

### Data and presentation conventions relevant to interpretation
- “Billion” means a thousand million; “trillion” means a thousand billion.
- “Basis points” refers to hundredths of 1 percentage point.
- Data refer to calendar years except where countries use fiscal years (see Table F in the Statistical Appendix).
- For some countries, figures for 2016 and earlier are based on estimates rather than actual outturns (see Table G in the Statistical Appendix).
- Composite country-group data represent calculations based on 90 percent or more of the weighted group data unless noted otherwise.
- If no source is listed on tables and figures, data are drawn from the WEO database.
- Minor discrepancies between sums of constituent figures and totals reflect rounding.

*Source: World Economic Outlook, April 2017 (text excerpt: assumptions, preface, and related analysis).*

### EXECUTIVE SUMMARY

### EXECUTIVE SUMMARY

### Global outlook and projections
- World growth is projected to rise from 3.1 percent in 2016 to 3.5 percent in 2017 and 3.6 percent in 2018.
- Activity is projected to pick up markedly in emerging market and developing economies as conditions in commodity exporters gradually improve, supported by a partial recovery in commodity prices; growth is projected to remain strong in China and many other commodity importers.
- In advanced economies, the pickup is primarily driven by higher projected growth in the United States, where activity was held back in 2016 by inventory adjustment and weak investment.
- Forecast revisions since the October 2016 WEO:
  - Advanced economies: projected growth revised upward in the United States, and the outlook improved for Europe and Japan based on a cyclical recovery in global manufacturing and trade that started in the second half of 2016.
  - Emerging market and developing economies: downward revisions for several large economies (especially in Latin America and the Middle East) reflecting adjustment to declines in terms of trade, oil production cuts, and idiosyncratic factors; 2017 and 2018 forecasts marked up for China and Russia.

### Recent developments and indicators
- The world economy gained speed in the fourth quarter of 2016 and the momentum is expected to persist.
- Economic activity gained momentum in the second half of 2016, especially in advanced economies; inventories began contributing positively to U.S. growth after five quarters of drag.
- Production of both consumer durables and capital goods rebounded in the second half of 2016.
- Forward-looking indicators, such as purchasing managers’ indices, suggest continued strength in manufacturing activity into early 2017.
- Global trade is showing signs of recovery after a long period of weakness, linked to a gradual global recovery in investment.
- Commodity markets:
  - The IMF’s Primary Commodities Price Index increased by 15 percent between August 2016 and February 2017.
  - Oil prices increased by some 20 percent between August 2016 and February 2017, in part due to the OPEC and other producers’ agreement to cut oil production.
- Inflation:
  - Headline inflation has been picking up in advanced economies due to higher commodity prices, but core inflation dynamics remain subdued and heterogeneous.
  - Headline inflation has also picked up in many emerging market and developing economies due to higher commodity prices, though in a number of cases it has receded as pass-through from sharp currency depreciations in 2015 and early 2016 fades.

### Risks (skewed to the downside, especially over the medium term)
- The balance of risks remains tilted to the downside, with pervasive uncertainty surrounding policies.
- Near-term upside potential exists from buoyant market sentiment, but a sharp increase in risk aversion is possible.
- Key downside risk factors listed in the source:
  - An inward shift in policies, including toward protectionism, with lower global growth caused by reduced trade and cross-border investment flows
  - A faster-than-expected pace of interest rate hikes in the United States, which could trigger a more rapid tightening in global financial conditions and a sharp dollar appreciation, with adverse repercussions for vulnerable economies
  - An aggressive rollback of financial regulation, which could spur excessive risk taking and increase the likelihood of future financial crises
  - Financial tightening in emerging market economies, made more likely by mounting vulnerabilities in China’s financial system associated with fast credit growth and continued balance sheet weaknesses in other emerging market economies
  - Adverse feedback loops among weak demand, low inflation, weak balance sheets, and anemic productivity growth in some advanced economies operating with high levels of excess capacity
  - Noneconomic factors, including geopolitical tensions, domestic political discord, risks from weak governance and corruption, extreme weather events, and terrorism and security concerns
- The risks are interconnected and can be mutually reinforcing (examples cited: inward policy shifts linked to geopolitical tensions and rising global risk aversion; noneconomic shocks harming confidence and market sentiment; faster tightening of global financial conditions or protectionism exacerbating capital outflow pressures in China).

### Policy priorities and recommendations
- Macroeconomic demand management should be increasingly differentiated according to cyclical positions:
  - In economies with slack and persistently weak core inflation, cyclical demand support remains necessary, including to stave off pernicious hysteresis effects.
  - In economies where output is close to or above potential, fiscal policy should aim at strengthening safety nets and increasing potential output.
- Domestic policy actions:
  - Support demand and repair balance sheets where necessary and feasible.
  - Boost productivity, labor supply, and investment through structural reforms and supply-friendly fiscal measures.
  - Upgrade public infrastructure.
  - Support those displaced by structural transformations such as technological change and globalization.
  - Implement credible strategies to place public debt on a sustainable path.
  - For emerging market and developing economies: adjust to lower commodity revenues and address financial vulnerabilities.
- Structural reforms and inclusiveness:
  - Actions to bolster potential output are urgent given headwinds from population aging in advanced economies, adjustment to lower terms of trade, financial vulnerabilities in emerging market and developing economies, and sluggish total factor productivity growth.
  - Chapter findings summarized: wages have not kept up with productivity in many economies over much of the past three decades, leading to a decline in labor’s share of national income; technological change has been the dominant driver of the labor share in advanced economies, whereas trade integration has been the dominant driver in emerging market economies.
  - Possible policy levers to make growth more inclusive include more progressive taxation; investments in skills, lifelong learning, and high-quality education; and measures to enhance occupational and geographical mobility of workers.

### Role of multilateral cooperation
- Many global challenges call for individual country actions supported by multilateral cooperation.
- Key areas for collective action include preserving an open trading system; safeguarding global financial stability; achieving equitable tax systems; continuing to support low-income countries pursuing development goals; and mitigating and adapting to climate change.
- Preserving the global economic expansion requires policymakers to avoid protectionist measures and to do more to ensure that gains from growth are shared more widely.

*Source: EXECUTIVE SUMMARY (text - EXECUTIVE SUMMARY), World Economic Outlook: Gaining Momentum?, April 2017*

### 4. Advanced Economies

### 4. Advanced Economies

### Global activity and GDP growth
- Global economic activity gained momentum in the fourth quarter of 2016.
- Manufacturing PMIs and consumer confidence increased noticeably in advanced economies in late 2016 and early 2017; they recovered to a more modest extent in emerging market economies.
- Production:
  - Production of both consumer durables and capital goods recovered in late 2016 after several quarters of lackluster growth or contraction.
- Real import growth picked up in the second half of 2016, consistent with firming investment.

### Commodity prices and inflation
- Oil and energy:
  - Oil prices stood at about $50 a barrel as of end-March, still some 12 percent stronger than in August 2016.
  - Natural gas: as of February 2017 the average price for Europe, Japan, and the United States was up by about 19 percent relative to August 2016.
  - Coal: average of Australian and South African prices in February 2017 was more than 20 percent higher than in August 2016.
  - Global capital expenditures in oil and gas industries and world oil production growth showed evolving dynamics (figures referenced).
- Other commodities:
  - Metal prices have increased by 23.6 percent.
  - Agricultural commodity prices increased by 4.3 percent; food prices rose by 4.9 percent.
- Inflation developments:
  - The increase in commodity prices contributed to a recovery in global inflation since August.
  - China’s producer prices have emerged from deflation after four years.
  - Global consumer price inflation has ticked up as retail gasoline and other energy-related prices increased.
  - In advanced economies, 12-month consumer price inflation in February stood slightly above 2 percent (more than double the average annual inflation rate of 0.8 percent in 2016).
  - Core inflation has increased much less—if at all—and remains well below central bank targets in almost all advanced economies.
  - In emerging market economies, the revival in headline consumer inflation is more recent as higher fuel prices have only recently outweighed earlier exchange-rate depreciation effects.
  - Near- and longer-term inflation expectations remain subdued; survey-based consumer price inflation expectations for 2017 have only very recently stopped falling for advanced economies, and expected inflation for the next 10 years has only recently registered an increase after declining steadily in 2015 and 2016.

### Financial market developments
- Market sentiment strengthened since August 2016, reflecting positive outlook data and expectations of U.S. fiscal stimulus, higher infrastructure investment, and deregulation.
- Interest rates and monetary policy:
  - With stronger expected future demand, long-term nominal and real interest rates have risen substantially since August 2016, especially since the U.S. elections in November.
  - As of end-March, nominal yields on 10-year U.S. Treasury bonds had increased by some 85 basis points compared with August and 55 basis points compared with just before the U.S. election.
  - Long-term rates increased sharply in the United Kingdom as well; the increase in core euro area long-term yields after August was more moderate—about 40 basis points in Germany—but Italian yields rose about 120 basis points.
  - The U.S. Federal Reserve raised short-term interest rates in December 2016 and March 2017. Markets priced in two additional rate increases by the end of 2017 or early 2018.
  - In most other advanced economies, the monetary policy stance remained broadly unchanged.
- Equities and valuations:
  - Equity markets in advanced economies registered sizable gains amid strengthening consumer confidence and positive macroeconomic data.
  - Gains have been notable in sectors exposed to potential fiscal stimulus and for financial stocks; higher valuations of financial stocks reflect favorable impacts of steepening yield curves and higher growth on expected profitability, but also potential downside risks from possible rollback of financial regulation in the United States.
- Exchange rates and capital flows:
  - The U.S. dollar strengthened in real effective terms by about 3.5 percent between August 2016 and late March 2017; the euro and especially the Japanese yen weakened.
  - The U.S. dollar, Korean won, Taiwanese dollar, and Australian dollar strengthened in real effective terms since August; the Turkish lira and Malaysian ringgit depreciated in real effective terms, while the Indian rupee and currencies of some commodity-exporting emerging market economies—particularly the Russian ruble—gained.
  - The Mexican peso strengthened in recent weeks and stood little changed relative to August.
  - Preliminary data pointed to sharp nonresident portfolio outflows from emerging markets in the wake of the U.S. election, following a few months of solid inflows, but a turnaround in more recent weeks.

### Key forces shaping the outlook for advanced economies
- Major drivers differ across country groups:
  - United States: projected to gather steam as a result of expansionary fiscal policy.
  - Europe and other advanced economies: cyclical recovery from the crises of 2008–09 and 2011–12 will help keep growth modestly above potential over the next few years.
- Medium-term constraints:
  - Demographic headwinds and weak trend productivity are likely to restrain medium-term growth.
  - For emerging market and developing economies, adjustment to lower commodity prices and slowing productivity growth are key medium-term challenges.

### Continued cyclical recovery in advanced economies
- Recovery status:
  - The recovery from the crises of 2008–09 and 2011–12 is ongoing in many advanced economies; output remains below potential and unemployment remains above 2008 levels in many countries.
  - The cyclical rebound has been slow, reflecting gradual repair of impaired balance sheets, temporarily high private and public sector savings, weakening of monetary policy transmission, and fiscal tightening between 2011 and 2015 that dampened the postcrisis recovery.

*Source: Chapter 1, "Global Prospects and Policies", World Economic Outlook, April 2017.*

### 2. Real Policy Rates

### 2. Real Policy Rates

### Evolution of financial market conditions and capital flows
- Long-term government bond yields in local currency rose together with bond yields in advanced economies after the U.S. election in November, but have since retreated in most countries. (Data are through March 31, 2017.)
- Net flows into emerging market funds turned negative in the immediate aftermath of the November 8 election in the United States, but were positive in the first three months of 2017.
- Capital inflows into emerging market economies declined somewhat in the third quarter of 2016 while capital outflows picked up modestly; both were little changed in the fourth quarter of 2016.
- Reserves continue to decline for the group, driven largely by continued reserve decumulation in China.

### Equity, credit, and heterogeneity across emerging market economies
- Equity prices are up, relative to August, in most emerging market economies (Emerging Europe; China; Emerging Asia excluding China; Latin America).
- Credit dynamics are heterogeneous across emerging market economies.
- Notes on coverage and definitions:
  - Emerging Asia excluding China comprises India, Indonesia, Malaysia, the Philippines, and Thailand.
  - Emerging Europe comprises Poland, Romania, Russia, and Turkey.
  - Latin America comprises Brazil, Chile, Colombia, Mexico, and Peru.
  - Credit is other depository corporations’ claims on the private sector (from IFS), except: Brazil private sector credit is from the Monetary Policy and Financial System Credit Operations published by Banco Central do Brasil; China credit is total social financing after adjusting for local government debt swap.

### Terms-of-trade shocks and commodity exporters
- The slowdown in China—along with commodity price fluctuations—has been the key driver of economic performance in emerging market and developing economies, especially in commodity exporters.
- For emerging market and developing economies as a group, the decline in growth between 2011 and 2016 was 2.2 percentage points, with about two-thirds of this decline attributable to weaker growth in commodity exporters.
- Commodity exporters account for most of the projected pickup in emerging market and developing economy growth in 2017–19, though their projected recovery is modest relative to their sharp decline over the previous five years.
- Low-income developing countries: the lion’s share of the 1.6 percentage point decline in growth between 2011 and 2016 is attributable to the drastic slowdown in Nigeria; Nigeria in 2016 accounted for more than 20 percent of purchasing-power-parity GDP of low-income countries and about half of the GDP of commodity exporters in this country group.
- Commodity exporters suffered sizable income losses during 2015 and 2016. Commodity price forecasts suggest some recovery in prices during 2017 and beyond, but forecast gains are expected to be much more modest than the losses already incurred—implying a protracted adjustment for many commodity exporters.
- The need for a protracted period of fiscal consolidation is cited as an important reason the recovery in commodity exporters is forecast to be subdued.

### Productivity headwinds and total factor productivity (TFP)
- Medium-term growth rates will be shaped largely by the pace of total factor productivity growth; the WEO incorporates a gradual recovery in TFP growth rates from recent weak levels.
- TFP growth is projected to stay below the pace registered before the global financial crisis, especially in emerging market economies.
- Total factor productivity slowed sharply following the 2008–09 crisis, both in advanced and emerging market economies. While some recovery is expected, productivity growth is not projected to return to its precrisis pace.
- A key factor behind the slowdown has been weak investment—and the associated slow pace of adoption of capital-embodied technologies. The drop in investment was abrupt and sustained in advanced economies, but more gradual in emerging market economies.
- Drivers contributing to subdued TFP growth include: legacies of the financial crisis (high corporate debt and nonperforming loans constraining investment), increased misallocation of capital, waning effects of earlier ICT adoption, population aging, decelerating global trade integration, slowing human capital accumulation, and taxation policies.

### Policy assumptions and forecasted policy paths
- Fiscal policy:
  - After providing mild support in 2016, fiscal policy at the global level is projected to be broadly neutral in 2017 and 2018.
  - Among advanced economies, the fiscal stance (measured by the fiscal impulse) in 2017 is forecast to be expansionary in Canada, France, and Germany; contractionary in Australia, Korea, and the United Kingdom; and broadly neutral in Japan and the United States.
  - In emerging market and developing economies as a group, fiscal adjustment is expected to detract slightly from economic activity in 2017 and 2018, with marked differences across countries and regions.
  - The U.S. fiscal deficit is assumed to widen by 2 percentage points of GDP by 2019, which entails a fiscal impulse of 1 percent of GDP, with about equally sized decreases in the personal and corporate income tax burdens, concentrated in 2018 and 2019, and no change in infrastructure spending for the time being.
- Monetary policy:
  - The forecast assumes a less gradual normalization of policy interest rates in advanced economies than projected in the October 2016 WEO, particularly in the United Kingdom and the United States.
  - With the anticipated widening of the U.S. fiscal deficit, monetary policy is projected to be moderately less accommodative because of stronger demand and inflation pressure.
  - The U.S. policy interest rate is projected to rise by 75 basis points in 2017 and 125 basis points in 2018, reaching a long-term equilibrium rate of just below 3 percent in 2019.
  - In other advanced economies, the forecast assumes that monetary policy will remain very accommodative: short-term rates are projected to remain negative in the euro area through 2018 and close to zero in Japan over the forecast horizon.
  - Monetary policy stances across emerging market economies vary, reflecting diverse cyclical positions.

### Policy priorities and recommendations (as indicated in the text)
- Policy actions to accelerate the cleanup of balance sheets and demand support would help entrench the recovery in countries operating with significant excess capacity.
- For commodity exporters facing protracted adjustment, fiscal consolidation is necessary to address revenue shortfalls tied to commodity prices.

*Source: text - 2. Real Policy Rates (PDF chapter), World Economic Outlook: Gaining Momentum?, International Monetary Fund | April 2017.*

### 2. Change in the Structural Fiscal Balance

### 2. Change in the Structural Fiscal Balance

### Global fiscal stance and diversity across countries
- Fiscal policy is projected to be broadly neutral at the global level in 2017 and 2018, but this overall neutral stance masks considerable diversity across countries.
- Source: IMF staff estimates.
- Note: AEs = advanced economies; EMDEs = emerging market and developing economies.

### Other assumptions shaping the forecast
- Global financial conditions are assumed to remain accommodative, though somewhat tighter than forecast in the October 2016 WEO.
- Easing of lending conditions in major economies is expected to offset the anticipated rise in interest rates.
- Normalization of monetary policy in the United States and the United Kingdom is assumed to proceed smoothly, without triggering large and protracted increases in financial market volatility.
- Most emerging markets are expected to face generally accommodative financial conditions, with higher policy rates partially offset by a recovery in risk appetite, reflected in declines in sovereign bond spreads and upticks in most equity markets.
- Forecast incorporates a firming of commodity prices:
  - Oil prices are expected to rise to an average of $55 a barrel in 2017–18, compared with an average of $43 a barrel in 2016.
  - Nonfuel commodity prices, particularly metals, are expected to strengthen in 2017 relative to their 2016 averages.
- Negotiations on future U.K.–EU economic relations are assumed to proceed without raising excessive uncertainty and to settle in a manner that avoids a very large increase in economic barriers.

### Global outlook for 2017–18 (key projections)
- World growth:
  - 2016: 3.1 percent (estimated as in the October 2016 WEO)
  - 2017: 3.5 percent (projected)
  - 2018: 3.6 percent (projected)
  - 2017 projection is an upward revision of 0.1 percentage point relative to October 2016.
- Contribution to near- and medium-term pickup in global growth is projected to stem mainly from emerging market and developing economies.

### Growth outlook by country groups and medium term
- Advanced economies (group):
  - Growth in 2017 and 2018: 2.0 percent in each year
  - This is 0.2 percentage point higher than expected in October 2016.
- Emerging market and developing economies (group):
  - 2016: 4.1 percent (estimated)
  - 2017: 4.5 percent (projected)
  - 2018: 4.8 percent (projected)
- Medium-term global growth:
  - Projected to reach 3.8 percent by 2022.
  - Emerging market and developing economies projected to increase to 5 percent by the end of the forecast period.

### Growth outlook for individual advanced economies (selected)
- United States:
  - 2017: 2.3 percent (projected)
  - 2018: 2.5 percent (projected)
  - Potential growth estimated at 1.8 percent.
- Euro area:
  - 2017: 1.7 percent (projected)
  - 2018: 1.6 percent (projected)
  - Country forecasts: Germany 1.6 percent (2017) and 1.5 percent (2018); Italy 0.8 percent (2017 and 2018); Spain 2.6 percent (2017) and 2.1 percent (2018); France 1.4 percent (2017) and 1.6 percent (2018).
- United Kingdom:
  - 2017: 2.0 percent (projected)
  - 2018: 1.5 percent (projected)
  - Forecast revisions: 0.9 percentage point upward revision to 2017 and 0.2 percentage point downward revision to 2018 relative to prior forecasts.
- Japan:
  - 2016: 1.0 percent (growth estimate after comprehensive revision)
  - 2017: 1.2 percent (projected)
- Other advanced economies (selected):
  - Switzerland: 1.4 percent (2017) and 1.6 percent (2018).
  - Sweden: 2.7 percent (2017) and 2.4 percent (2018).
  - Commodity-exporting advanced economies: Norway 1.2 percent (2017); Canada 1.9 percent (2017); Australia 3.1 percent (2017).
  - Advanced economies in Asia (selected): Hong Kong SAR 2.4 percent (2017); Taiwan Province of China 1.7 percent (2017); Singapore 2.2 percent (2017); Korea 2.7 percent (2017).

### Growth outlook for emerging market and developing economies (selected)
- China:
  - 2017: 6.6 percent (projected)
  - 2018: 6.2 percent (projected)
  - 2017 forecast is 0.4 percentage point higher than in the October 2016 WEO; 2018 forecast is 0.2 percentage point higher.
- India:
  - 2017: 7.2 percent (projected; trimmed by 0.4 percentage point due to temporary shocks)
  - Medium-term growth: about 8 percent.
- ASEAN-5 (2017 projections):
  - Indonesia: 5.1 percent
  - Malaysia: 4.5 percent
  - Philippines: 6.8 percent
  - Vietnam: 6.5 percent
  - Thailand: projected to recover from a temporary dip in late 2016.
- Latin America and the Caribbean (region):
  - 2017: 1.1 percent (projected)
  - 2018: 2.0 percent (projected)
  - These are 0.5 and 0.2 percentage point lower, respectively, than in the October 2016 WEO.
  - Mexico: 2017: 1.7 percent; 2018: 2.0 percent. Cumulative downgrade over two years: 1.2 percentage point.
  - Brazil: 2017: 0.2 percent; 2018: 1.7 percent.
  - Argentina: 2017: 2.2 percent; 2018: 2.3 percent.
  - Venezuela: 2017: -7.4 percent; 2018: -4.1 percent.
  - Chile: 2017: 1.7 percent.
  - Colombia: 2017: 2.3 percent.
- Commonwealth of Independent States (region):
  - 2017: 1.7 percent (projected; 0.3 percentage point higher than October 2016 forecast).
  - Russia: 2017: 1.4 percent (projected).
  - Kazakhstan: 2017: 2.5 percent (projected; 1.9 percentage points higher than in October).
  - Ukraine: 2017: 2 percent (projected).
- Emerging and developing Europe (group):
  - 2017: 3.0 percent (projected)
  - 2018: 3.3 percent (projected)
  - Turkey: 2017: 2.5 percent (projected).
- Sub-Saharan Africa (region):
  - 2016: - (region contracted overall in 2016; specifics noted)
  - 2017: 2.6 percent (projected)
  - 2018: 3.5 percent (projected)
  - Nigeria: 2016: -1.5 percent (contraction); 2017: 0.8 percent (projected).
  - South Africa: 2017: 0.8 percent (projected).
  - Angola: 2017: 1.3 percent (projected).

*Source: International Monetary Fund, World Economic Outlook, April 2017.*

### CHAPTER 1

### CHAPTER 1

### Regional outlook: Middle East, North Africa, Afghanistan, and Pakistan
- Growth for the region is forecast to be 2.6 percent in 2017, 0.8 percentage point lower than projected in the October 2016 WEO.
- Drivers and country specifics:
  - Slower headline growth in oil exporters driven by the November 2016 OPEC agreement to cut oil production, which masks expected pickup in non-oil growth as fiscal adjustment to structurally lower oil revenues slows.
  - Continued strife and conflict in many countries detract from economic activity.
  - Saudi Arabia: growth expected to slow to 0.4 percent in 2017 because of lower oil production and ongoing fiscal consolidation, before picking up to 1.3 percent in 2018.
  - Other GCC countries: growth rates projected to dip in 2017.
  - Oil importers in the region: activity expected to accelerate, with growth rising from 3.7 percent in 2016 to 4.0 percent in 2017 and 4.4 percent in 2018.
  - Pakistan: growth forecast at 5 percent in 2017 and 5.2 percent in 2018, supported by ramped-up infrastructure investment.
  - Egypt: reforms expected to lift growth from 3.5 percent in 2017 to 4.5 percent in 2018.

### Inflation outlook for 2017–18
- Broad-based increase in headline inflation rates projected in both advanced and emerging market and developing economies with the uptick in commodity prices.
- Advanced economies:
  - For the advanced group as a whole, inflation is forecast to be 2.0 percent in 2017, up from 0.8 percent in 2016, and to stabilize at about that level over the next few years.
  - United States: consumer price inflation picking up from 1.3 percent in 2016 to a projected 2.7 percent in 2017. Core inflation expected to reach 2 percent personal consumption expenditure inflation by 2018 as slack diminishes and wage growth strengthens.
  - Euro area: inflation picking up to about 1.7 percent in 2017 from 0.2 percent in 2016; headline inflation projected to gradually approach the ECB objective of below but close to 2 percent, reaching 1.9 percent in 2022.
  - Japan: higher energy prices, yen weakening, and slowly building wage-price pressures expected to lift inflation, but inflation rates projected to stay well below the Bank of Japan’s target throughout the forecast horizon.
  - United Kingdom: inflation projected to increase to 2.5 percent in 2017 before gradually subsiding to the Bank of England’s target of 2 percent in the next few years.
  - Average headline inflation expected to return to positive territory in Singapore and Switzerland in 2017.
- Emerging market and developing economies (excluding Argentina and Venezuela):
  - Inflation projected to rise to 4.7 percent in 2017 from 4.4 percent in 2016, mostly reflecting higher commodity prices.
  - China: inflation expected to pick up to 2.4 percent in 2017 and to 3 percent over the medium term as slack in industry and downward pressure on goods prices diminish.
  - Mexico and Turkey: pickup in inflation in 2017 reflecting gasoline price liberalization in Mexico and significant currency depreciations in both countries.
  - Brazil and Russia: inflation expected to continue to decline, reflecting negative output gaps and dissipation of past currency depreciation effects, supply shocks, and/or administrative price increases.
  - Several large sub-Saharan African economies (for example, Nigeria, Angola, Ghana): inflation in 2017 expected to remain at double-digit levels, reflecting pass-through of large depreciations among other factors.

### External sector outlook and trade
- Global trade:
  - Estimated to have grown by 2.2 percent in 2016 in volume terms, the slowest pace since 2009, and below the 2.4 growth rate of world GDP at market exchange rates.
  - After declining to about ¼ percent in 2015, trade growth in emerging market and developing economies rose to an estimated 2.2 percent in 2016.
  - Global trade projected to grow at a rate of close to 4 percent in 2017–18 (close to 1 percentage point above world growth at market exchange rates), as demand and especially capital spending recover.
- Drivers of recent trade dynamics:
  - Slower exports and imports in advanced economies contributed to the 2016 slowdown.
  - Weak trade growth related to an investment slowdown and inventory adjustment, especially during the first part of 2016.
  - Recovery in trade underpinned by stronger trade growth in China and India and moderation of import contractions in Russia and the Commonwealth of Independent States.
  - Gradual recovery in investment by commodity exporters expected to boost import growth in 2017–18.

### Current account balances and international investment positions (IIP)
- Global current account imbalances:
  - Preliminary data suggest global current account imbalances in 2016 narrowed marginally.
  - In 2016, current account balances tended to increase in debtor countries and decrease in creditor countries, moving in a stabilizing direction.
  - Global current account forecasts indicate broad stability of imbalances in 2017 but a widening of deficits starting in 2018, as a projected fiscal expansion would lead to stronger domestic demand in the United States and a higher current account deficit.
- Country and regional developments in 2016:
  - Fuel exporters (creditors): current account balance worsened slightly, reflecting further decline in oil prices.
  - China: current account surplus contracted.
  - Japan: current account surplus increased, driven primarily by a sharp decline in the volume and price of energy imports.
  - Debtor countries with strengthened current account balances: nonfuel-exporting Latin American countries (reflecting weak domestic demand on imports), emerging Asia, and euro area debtor countries (helped by further terms-of-trade gains).
- Net international investment positions:
  - Creditor and debtor positions are estimated to have widened in 2016 and are projected to widen further over the medium term in relation to world GDP.
  - On the debtor side, the increase is explained entirely by rising net external liabilities in the United States, where the current account deficit is projected to widen over the next few years.
  - Net external liabilities are projected to shrink further in euro area debtor countries.
  - Among creditor countries, the increase in net external claims reflects projected continuation of large current account surpluses in European creditor countries and in advanced Asian economies.
  - Specific projected changes (2016–22, as share of domestic GDP):
    - Further growth in creditor positions among European creditor countries and advanced economies in Asia in the range of 25–30 percentage points of GDP.
    - Largest reduction in net liabilities among debtor countries projected for euro area debtor countries (over 18 percentage points of GDP).
    - Projected deterioration in the U.S. net external position of about 8 percentage points of GDP.
- Measurement and interpretation challenges:
  - Net IIP assessment complicated by corporate financial decisions, e.g., Ireland’s 2015 relocation of balance sheets and intellectual property products leading to an about €300 billion upward revision in intangible capital and a corresponding increase in Irish net external liabilities (exceeding 200 percent of GDP), as well as a sharp upward revision to growth.
  - Valuation changes from exchange rates and asset prices have materially affected net positions (for example, U.S. dollar appreciation reducing dollar value of U.S. external assets; pound depreciation boosting domestic-currency value of foreign-currency assets in the United Kingdom).

### Global rebalancing and growth composition
- Contribution to growth from domestic demand versus net external demand:
  - After the global financial crisis, growth of creditor countries in aggregate exceeded that of debtor countries, reflecting rapid growth in China.
  - During 2015–16, the contribution of net external demand to growth:
    - Declined in China, smaller advanced Asian economies, and European creditor countries.
    - Increased in Japan and especially in oil exporters, where contracting domestic demand reduced import demand.
  - Among debtor countries:
    - Latin America displayed a pattern similar to oil exporters (domestic demand contraction, net external demand supporting growth).
    - Net external demand supported growth in euro area debtor countries, though less than during 2010–14 due to domestic demand recovery.
- Policy implications for rebalancing:
  - Shifting macroeconomic policies and exchange rate movements could widen flow imbalances and expand stock imbalances.
  - Stronger reliance on domestic demand in some creditor countries, especially those with policy space, would help sustain world growth and facilitate global rebalancing.
  - In the United States, fiscal policy measures that gradually enhance productive capacity along with demand, anchored in a medium-term fiscal consolidation plan to reduce the rising public debt-to-GDP ratio, would produce a more sustained growth impact and help contain external imbalances.

### Risks
- WEO growth forecasts represent the IMF staff’s modal scenario; risks remain tilted to the downside. 

*Source: CHAPTER 1, WORLD ECONOMIC OUTLOOK: GAINING MOMENTUM? (International Monetary Fund | April 2017).*

### CHAPTER 1

### CHAPTER 1  GLObaL PROsPECTs aND POLICIEs

### Risks to the Baseline Forecast
- Risks remain tilted to the downside, more so over the medium term; near-term upside potential has risen in recent months.
- Short-term upside sources:
  - Gains in business and consumer sentiment in advanced economies since last fall, as reflected in survey outcomes and equity prices.
  - Possibility of policy easing greater than assumed in the baseline in the United States and China.
  - Baseline for the United States does not incorporate additional public infrastructure investment (pending specifics).
- Downside sources: five primary areas of uncertainty, most pointing to downside risks relative to the baseline.

### Disruption of Global Trade, Capital Flows, and Migration
- Structural and distributional forces:
  - Loss of middle-skill jobs in advanced economies since the early 1990s due to technological change.
  - Slow recovery from the crises of 2008–09 and 2011–12, with income distribution favoring highest earners, leaving little room for lower-income groups to advance.
  - Growing disillusionment with globalization in the United States and parts of Europe.
- Policy risks:
  - Protectionist policy actions in response to equity concerns could trigger higher tariffs or other trade barriers, with possible retaliatory responses.
  - In the United States, authorities have declared intention to reopen existing trade agreements; outcomes could be mutually beneficial if well executed or harmful if protectionist.
  - In Europe, coming elections may provide a platform for protectionist tendencies.
- Economic effects of higher trade barriers:
  - Raising barriers to trade would reduce aggregate output and lower well-being.
  - A country that hikes tariffs can expect its price level to rise and output to fall, especially if partners retaliate (Scenario Box 1, October 2016 WEO).
  - Broad-based increase in import costs would dent global output; damage could be larger given increasing fragmentation of production processes across countries (Koopman, Wang, and Wei 2014; Yi 2003, 2010).
  - Higher import costs disproportionately harm purchasing power of lower-income groups in advanced economies (Fajgelbaum and Khandelwal 2016).
  - Persistent, protection-induced reduction of trade could harm supply-side potential via weaker competitive pressures to innovate and slower cross-border diffusion of new technologies.
  - Curtailing immigration flows would hinder skill specialization in advanced economies, limiting productivity and income growth over the long term (Chapter 4 of the October 2016 WEO).
- Multilateral cooperation risk:
  - Disruption of international economic linkages could lead to a generalized decline in cross-border cooperation, making coordinated solutions to multilateral challenges more elusive and magnifying output costs of negative shocks.
- Recent observations:
  - So far, signs of an inward-looking tilt have not had a noticeable impact on economic sentiment indicators in advanced economies (example: private sector confidence and spending in the United Kingdom remained resilient after the Brexit vote).
  - Growing salience of future increases in trade costs will likely gradually dampen expectations of future real earnings and weigh on investment and hiring.
  - Negotiations on new trade agreements, if drawn out, could increase uncertainty and magnify headwinds (case in point: Mexico, where financial market conditions tightened because of fears of protectionist policy changes in the United States).

### The U.S. Policy Agenda
- Key uncertainties: size and composition of any fiscal policy easing, and impact of possible reform of the corporate tax system (toward destination-based cash flow taxation).
- U.S. fiscal policy stance:
  - April 2017 WEO projections prepared before crucial details of U.S. fiscal policy changes were known.
  - Uncertainty around U.S. actions and their effects on aggregate demand, potential output, government budget deficit, and value of the U.S. dollar implies wide upside and downside risks to the baseline for the United States and global spillovers.
  - Two illustrative stylized scenarios (Scenario Box 1):
    - Both scenarios: U.S. output rises above the baseline path, an output gap opens up, monetary policy tightens, the U.S. dollar appreciates, and the U.S. current account deficit widens given increased U.S. permanent income.
    - First case: stronger impact on potential output; effects generally stronger (larger increase in U.S. imports that initially benefits other economies).
    - Second case: more limited increase in potential output; faster normalization in U.S. and global term premia leads to larger increases in global interest rates and sharper tightening in financial conditions, offsetting U.S. import boost and harming foreign output.
    - Fiscal adjustment is undertaken five years into the simulation horizon in both scenarios to stabilize public debt; the required contraction in the primary deficit is larger in the second scenario.
  - Additional considerations not captured in simulations:
    - Upside: productivity gains in the United States could spill over to other economies, boosting permanent incomes and demand, tempering widening U.S. current account deficit and global interest rate increases.
    - Downside: initial dollar appreciation could generate stress among emerging market economies with de jure or de facto currency pegs to the U.S. dollar and/or balance-sheet currency mismatches.
    - A growth-friendly fiscal policy implemented in a deficit-neutral way would lead to an even higher long-term level of GDP (as noted in Scenario Box 1).
  - Overall: simulations point to downside risks associated with deficit-financed U.S. fiscal policy easing, especially in the medium term; ultimate impact depends on whether measures lift U.S. potential output, with possible negative international repercussions via tighter global financial conditions.
- U.S. corporate tax reform:
  - The U.S. corporate tax system is characterized in the source as too complex, narrow base and marginal rate too high, with legislated exemptions, debt-financing bias, and incentives for cross-border avoidance and tax planning.
  - Proposal under discussion: replace corporate income tax with a destination-based cash flow tax (discussed in Box 1.1 of the Fiscal Monitor).
  - Expected effects of destination-based cash flow tax with full and immediate expensing:
    - Meaningfully boost U.S. business investment and output.
    - Generate strong incentives for profit and production shifting into the United States, creating large international spillovers; other countries might take measures to protect tax bases or also move toward destination-based taxation.
    - Raise U.S. household saving rate and put downward pressure on global interest rates.
    - Limited effects on U.S. competitiveness in practice: border adjustment (exempting exports from revenues and disallowing deduction of import costs) would in simplest textbook case strengthen the dollar relative to all other currencies and/or raise domestic prices and wages, leaving the trade balance unchanged.
    - A sharp appreciation of the U.S. dollar would generate deflation pressure in economies whose currencies are tied to the U.S. dollar and could impose financial stress on countries with significant currency mismatches in private or public balance sheets.
    - Border adjustment may be inconsistent with existing World Trade Organization rules, potentially leading to trade disputes and risks to the open trading system.

### Financial Deregulation
- Postcrisis reforms have strengthened oversight, raised capital and liquidity buffers, and improved cooperation among regulators (Chapter 1 of the April 2017 GFSR).
- Risks of backtracking:
  - Wholesale dilution or backtracking on reforms would raise the probability of costly financial crises in the future.
  - Deregulation in one country may lead to deregulation in others in a highly interconnected international financial system.
  - Failure to complete the global reform agenda and allowing regulatory fragmentation across borders would hurt countries outside central standard-setting bodies, particularly emerging market economies that rely heavily on strong global standards to level the playing field and support financial stability amid rising domestic threats.

### Tightening of Economic and Financial Conditions in Emerging Market Economies
- Role in recent global growth revisions:
  - Emerging market and developing economies have accounted for the bulk of downward revisions to global growth in recent years.
  - Most downward revisions occurred in China and India, especially during 2011–13; in commodity exporters following the 2015–16 plunge in oil prices; and, to a lesser extent, in Middle Eastern economies suffering from conflict (see Box 1.1).
- Recent volatility and vulnerabilities:
  - Many emerging market economies have experienced bouts of financial volatility in recent years.
  - Some large commodity exporters and other stressed economies have faced substantial exchange rate movements; China swung from net capital inflows to sizable net outflows.
  - Tightening of financial conditions across emerging markets after the U.S. election highlighted persistent vulnerability to sudden shifts in global market sentiment.

### Risks from Continued Rapid Credit Expansion in China
- Policy stance and vulnerabilities:
  - Chinese authorities are expected to maintain emphasis on protecting macroeconomic stability in the run-up to the leadership transition later this year.
  - Progress with demand-side rebalancing and reducing excess industrial capacity has continued, but reliance on stimulus measures and dangerous dependence on rapidly expanding credit remain.
  - Credit is intermediated through an increasingly opaque and complex financial system.
- Recent market developments:
  - Return of capital outflows reflecting expectations of renminbi depreciation and narrowing yield differentials as global interest rates increased.
  - Chinese equity markets remained tranquil compared with prior turmoil in August 2015 and January 2016, but bond markets have seen bouts of turbulence.
  - People’s Bank of China actions to tighten short-term liquidity pushed up repurchase arrangement rates in late 2016, causing losses for leveraged bond investors and pushing up bond yields sharply; segments of the repurchase arrangement market began to seize up, prompting broad-based liquidity support in December 2016.
- Baseline assumption and risks:
  - Baseline forecast assumes limited progress in tackling the corporate debt overhang and reining in credit, and a policy preference for maintaining relatively high GDP growth in the near term.
  - Persistent resource misallocation raises the risk of a disruptive adjustment in China in the medium term.
  - External triggers—such as a shift toward protectionism in advanced economies or domestic shocks—could lead to broader tightening of financial conditions in China, possibly exacerbated by capital outflow pressures, adversely impacting demand and output.
  - Spillovers from turbulence in China can be large, operating mainly through commodity prices and global financial risk aversion (Chapter 4 of the October 2016 WEO).

### Vulnerabilities in Other Emerging Market and Developing Economies
- Comparisons with past episodes:
  - Compared with past capital inflow slowdowns, emerging market economies have seen fewer financial sector problems in recent years despite high corporate leverage and, in some cases, sharp losses in earnings from adverse terms-of-trade shifts (Chapter 2 of the April 2016 WEO).
- Sources of resilience and remaining fragilities:
  - Improved macroeconomic policy management and the beneficial role of exchange rate flexibility have helped smooth shocks.
  - Credit booms are waning in many economies (key exception: China); corporate leverage has in most cases peaked and continues to decline from a high level.
  - Underlying fragilities remain: corporate sector buffers could be wearing thin after periods of macroeconomic strains and financial volatility.
  - More generally, reduced profitability, still-elevated corporate debt, limited policy space, and other constraints increase vulnerability to future shocks.

*International Monetary Fund | April 2017*

### CHAPTER 1

### CHAPTER 1

### Global risks and vulnerabilities
- Weak bank balance sheets in some emerging market economies leave them potentially exposed to tighter global financial conditions, capital flow reversals, and the adverse balance sheet implications of sharp currency depreciations (Chapter 1 of the April 2017 GFSR).
- Strains could materialize if:
  - the projected fiscal policy easing in the United States proves more inflationary than expected, requiring a faster pace of monetary policy tightening and triggering a faster normalization of U.S. term premia; or
  - there is a marked shift toward protectionist policy actions in advanced economies.
- Recoveries in a relatively small number of stressed economies—most commodity exporters—account for an important portion of the global growth pickup in 2017–18; these recoveries could fall short of baseline projections if domestic reforms are delayed.
- Low-income commodity exporters with exhausted fiscal buffers face risk of disorderly conditions and weaker growth if policy adjustments are delayed.
- A reversal of foreign direct investment and other capital flows from China could strain low-income economies relying on such financing for infrastructure.

### Weak demand and balance sheet problems in parts of Europe
- Persistent weak demand in several advanced economies can work through three channels:
  - A downshift in inflation expectations, higher expected real interest rates, debt service difficulties, and negative feedback to demand.
  - Weak investment and slower adoption of capital-embodied technological change, lower productivity growth, and weaker expected profitability, reinforcing sluggish investment.
  - A prolonged period of high unemployment leading some job seekers to drop out of the workforce or become unemployable due to skill erosion.
- Although fears of debilitating cycles have receded somewhat amid firmer demand and steepening yield curves, parts of Europe still face:
  - incomplete cyclical recovery in output, employment, and inflation,
  - large burdens of nonperforming loans, and
  - banking system profitability challenged by structural features such as high costs and overbanking (Chapter 1 of the April 2017 GFSR).
- Policy failures to clean up balance sheets, consolidate and raise banking cost effectiveness, maintain demand, and enact productivity-enhancing reforms would perpetuate weak inflation dynamics and investment and leave these economies susceptible to self-reinforcing adverse feedback loops.
- As growth and core inflation prospects in core euro area economies strengthen, there is risk that euro area monetary policy tightens, weighing on recovery in countries with high unemployment and large output gaps.
- Sluggish income recovery can fuel inward-turn pressures and protectionist measures, further harming demand domestically and abroad.

### Noneconomic factors
- Rising geopolitical tensions, domestic strife, and idiosyncratic political problems burden regional outlooks; notable examples include civil wars and domestic conflicts in parts of the Middle East and Africa, refugee and migrant plights, and acts of terror worldwide.
- The baseline assumes gradual easing of tensions in many severely affected countries, but episodes may be more protracted and hold back recovery.
- Weak governance and large-scale corruption can undermine confidence and popular support, taking a heavy toll on domestic activity.
- Other factors weighing on growth include the persistent effects of a drought in eastern and southern Africa and the spread of the Zika virus; intensification would deepen hardship in directly affected countries, especially smaller developing economies (IMF 2016).
- Increased geopolitical tensions and terrorism could take a toll on global market sentiment and broader economic confidence.

### Fan chart and risk assessment
- A fan chart analysis—based on equity and commodity market data and dispersion of inflation and term spread projections of private sector forecasters—corroborates that risks remain skewed to the downside for 2017 and 2018.
- The analysis finds a narrower dispersion of outcomes around the current- and next-year baseline than a year ago, consistent with a more optimistic tone in financial markets and reduced uncertainty after the Brexit vote and the U.S. elections.
- Despite narrower dispersion, the balance of risks is tilted to the downside; the width of the 90 percent confidence interval has diminished for both current- and next-year growth forecasts, with a slightly greater decline for the upper part of the interval—pointing to a more pronounced downward skew than in October 2016.
- The probability of a recession over a four-quarter horizon (first quarter of 2017–fourth quarter of 2017) has declined in most regions relative to the October 2016 probability for the third quarter of 2016–second quarter of 2017.
- Drivers lifting the outlook include stronger cyclical momentum, anticipated U.S. fiscal stimulus, increased external demand, and rising commodity prices; deflation risks remain elevated for the euro area and Japan because pass-through of higher commodity prices to headline inflation is projected to fade and core inflation remains weak, especially in Japan.
- Figure and chart metrics preserved in source:
  - 90 percent confidence interval, 70 percent confidence interval, 50 percent confidence interval comparisons (current-year and next-year; April 2016, October 2016, April 2017 WEO).
  - Balance of risks depicted as coefficient of skewness for term spreads, S&P 500, inflation risk, and oil market risks.
  - Probability measures shown for recession (2017:Q2–2018:Q1) and deflation (2018:Q2) by region.

### Policy priorities (global)
- Global activity is picking up, but momentum is unlikely to be sustained without policymakers implementing appropriate policies and avoiding missteps.
- Continued demand support and well-targeted structural reforms to lift supply potential and broaden economic opportunities across the skills spectrum remain key.
- An overarching challenge is to safeguard global economic integration and the cooperative global economic order, which have been critical sources of productivity growth and resilience.
- Rolling back economic integration would not address distributional concerns largely attributable to technological change; heightened restrictions on trade and capital flows would impose broad economic costs and risk retaliation.
- Policy approach recommended:
  - Preserve gains from cross-border integration while ramping up domestic policies to share gains more broadly.
  - Short-term: active labor market policies combined with social safety nets to smooth income loss.
  - Longer-term: education, skill building and retraining, policies to facilitate reallocation (housing and credit access).
  - Progressive taxes and well-targeted transfer policies to finance these efforts (see Chapter 1 of the April 2017 Fiscal Monitor).

### Policies—Advanced economies
- Advanced economies as a group face modest current and prospective growth, sluggish productivity, low investment, and in some cases persistently low core inflation—reflecting subdued demand, diminished growth expectations, and aging populations.
- Cross-cutting need: lift potential output; cyclical conditions are heterogeneous across countries.
- Policy guidance by cyclical position:
  - Where output gaps are negative and wage pressures and inflation expectations are muted:
    - Monetary policy must remain accommodative, using unconventional strategies as needed to raise inflation expectations and lower real borrowing costs.
    - Fiscal support, calibrated to available space and oriented to protect the vulnerable and lift medium-term growth, remains essential.
    - If fiscal adjustment cannot be postponed, its speed and composition should minimize drag on output.
    - Support for demand must be accompanied by addressing corporate debt overhangs and repairing bank balance sheets (legacy nonperforming loans and operational efficiency) as discussed in October 2016 GFSR and October 2016 Fiscal Monitor.
  - Where output is close to or above potential:
    - Well-anchored inflation expectations should allow for gradual monetary policy normalization.
    - Fiscal policy adjustments depend on country circumstances and public debt dynamics; policy should strengthen safety nets and increase longer-term potential output.
- Structural reforms needed across advanced economies to enhance productivity, investment, and labor supply; country-specific priorities include:
  - Boost labor force participation through reforms to labor taxes and social benefits.
  - Well-targeted infrastructure investments.
  - Corporate income tax reform and tax incentives to boost research and development.
  - Investments in education and health care to improve human capital.
  - Elimination of product and labor market distortions to boost private sector dynamism.
  - Note: Removing barriers to entry into product and service markets can raise near-term activity, but labor market reforms may require supportive macroeconomic policies when the economy is weak (Chapter 3 of April 2016 WEO).

### Country-specific priorities
- United States:
  - Economy regained momentum in the second half of 2016 with strong job creation, solid disposable income growth, and robust consumer spending.
  - Economy is close to full employment; core personal consumption expenditure inflation is only slowly inching up toward the Federal Reserve’s 2 percent target, supporting gradual, data-dependent monetary tightening.
  - Policy recommendations:
    - A credible deficit- and debt-reduction strategy to open space for policies that improve social outcomes and lift productive capacity while putting the debt ratio on a downward path.
    - Fiscal stance should remain neutral in the current year; fiscal consolidation could start in 2018.
    - Structural and fiscal policies to upgrade public infrastructure, boost labor force participation, and enhance human capital.
    - Priorities: skill-based immigration reform, job training, paid family leave, child care assistance.
    - Comprehensive business tax reform geared toward simplification and fewer exemptions to encourage job creation and investment.
    - Financial regulation changes should avoid buildup of financial stability risks; strengthen regulation and supervision of non-bank financial institutions as activity shifts to less-regulated entities.
- Euro area:
  - With inflation expectations below target and several economies operating below capacity, the European Central Bank should maintain an accommodative stance; additional easing may be needed if core inflation fails to pick up.
  - Monetary policy will be more effective if supported by cleaning up balance sheets, strengthening the financial sector, using fiscal space where available, and accelerating structural reforms.
  - Specific priorities:
    - Accelerate banks’ balance sheet repair and resolution of nonperforming loans via supervisory encouragement, insolvency reform, and development of distressed debt markets.
    - Complete the banking union, including introducing a common deposit insurance program with a common effective fiscal backstop.
    - Greater centralized investment in public infrastructure to help countries with demand shortfalls that lack fiscal space or need to consolidate due to high and rising debt burdens.
    - Where consolidation is required, undertake it gradually and in a growth-friendly manner; in countries with fiscal space (such as Germany), use fiscal policy to bolster productive capacity and demand, reduce current account surpluses, support intra-euro-area rebalancing, and generate demand spillovers.
    - Exploit synergies between structural reforms and demand management; where demand is weak but fiscal space is lacking, budget-neutral fiscal support can enhance reform effects.
    - Product and labor market reforms to encourage business dynamism, raise labor force participation, and address labor market duality.
    - Complete the single market to boost productive capacity.
    - Facilitate refugee integration through swift asylum processing, language training, job search assistance, better recognition of migrants’ skills through credential systems, and support for migrant entrepreneurship.
- Japan:
  - Growth was stronger than expected in 2016; inflation appears to be bottoming out due to higher fresh food prices and fading downward pressure from earlier yen appreciation.
  - Net exports were the main driver of growth in 2016, with fiscal policy also supportive.
  - Despite a tightening labor market, wage demands are not stronger than in past few years and thus are unlikely to kindle much-needed positive wage-price dynamics.
  - The Bank of Japan’s monetary easing through asset purchases and negative deposit rates continues to be a key policy element.

*International Monetary Fund | April 2017*

### introduction of quantitative and qualitative easing

### introduction of quantitative and qualitative easing

### Japan: monetary accommodation, constraints, and comprehensive policy package
- Yield curve control, combined with quantitative and qualitative easing, "have been critical to preventing another bout of deflation, but the low and declining neutral real rate and low nominal rates constrain monetary policy effectiveness."
- Continued efforts to raise inflation expectations to further lower real rates remain necessary, including "through a further upgrade to the Bank of Japan’s communication framework."
- To attain a durable increase in inflation and growth, a comprehensive policy approach is needed that "enhances monetary accommodation with a supportive fiscal stance and reforms to labor market policies."
- Elements of the recommended package include:
  - Reforms to diminish labor market duality and increase labor force participation by women and older workers while admitting more foreign workers.
  - Lowering entry barriers in retail trade and services.
  - Improving the provision of capital for new ventures.
  - Supporting stronger corporate governance to discourage companies from accumulating excess cash reserves.
  - A credible fiscal consolidation over the medium term—based on a gradual preannounced increase in the consumption tax, social security reform, and a broadening of the tax base—remains critical.

### United Kingdom: Brexit exit and policy stance
- Principal challenge: "successfully navigate the exit from the European Union and negotiate the new arrangements for economic relations with the European Union and other trading partners."
- The adverse impact on medium-term output would be lower if the new arrangements limit new economic barriers.
- Current accommodative monetary policy stance is appropriate because "growth is expected to slow and domestic cost pressures to remain contained."
- Fiscal approach: "the envisioned path of steady but gradual fiscal consolidation and the moderate relaxation of the targets strike an appropriate balance between providing an anchor for medium-term objectives and allowing room for short-term maneuvering amid elevated uncertainty about the economic outlook."

### Emerging market and developing economies: external environment and policy orientation
- Recent external environment characterized by:
  - Generally sluggish demand from advanced economies.
  - A sharp correction in commodity prices followed by a recovery since the first quarter of 2016 (albeit to levels well below previous peaks).
  - Spells of relatively benign financial conditions interspersed with recurrent spikes in market volatility.
- Going forward, aspects likely to be less supportive:
  - Weaker potential output growth across advanced economies and possible increase in trade barriers could translate into generally subdued demand growth.
  - China's transition to slower, more sustainable, consumption- and services-based growth may weigh on commodity exporters.
  - External financial conditions likely to remain uncertain; "A gradual, generalized tightening is expected as U.S. monetary policy normalizes," accompanied by continued search for yield in emerging market opportunities.
  - Terms of trade may improve for a subset of emerging market and developing economies with the bottoming out of commodity prices, but export price outlook remains subdued compared with the past.
- Recommended policy orientation:
  - Protect trade integration, permit exchange rate flexibility, and ensure vulnerabilities from high external imbalances and public debt are contained to help sustain convergence.
  - Economies with large and rising nonfinancial debt, unhedged foreign liabilities, or heavy reliance on short-term borrowing should adopt stronger risk management practices and contain balance sheet mismatches.
  - Improve domestic governance, institutions, and the business environment to reduce country risk perceptions and counter expected tightening in global financial conditions.

### Country-specific priorities (summarized)
- China:
  - Near-term outlook strengthened with policy support ahead of leadership transition in late 2017.
  - Rebalancing advancing toward services and consumption, but heavy reliance on credit persists.
  - Macro policy mix should: accept slower, more sustainable growth; reduce pace of credit growth closer to that of nominal GDP; raise policy rates; cut off-budget public sector investment while increasing on-budget allocations for social assistance, health expenditure, unemployment benefits, and restructuring funds.
  - Structural reforms: deregulate sectors dominated by state-owned enterprises, decisively restructure unprofitable SOEs and replenish bank buffers once losses are accounted for, accelerate household residency reforms, rein in shadow products, and strengthen supervisory framework.
- India:
  - Strong growth owing to critical structural reforms, favorable terms of trade, and lower external vulnerabilities.
  - Post-November 2016 currency exchange initiative challenge: replace currency in circulation.
  - Policy focus: reduce labor and product market rigidities; consolidate disinflation through agricultural reforms and infrastructure enhancements; boost financial stability via full recognition of nonperforming loans and raising public sector banks’ capital buffers; secure public finances through continued subsidy reduction and structural tax reforms, including implementation of the recently approved nationwide goods and services tax.
- Brazil:
  - Pace of contraction diminished, but investment and output had yet to bottom out at end-2016; fiscal crises in some states deepen.
  - Inflation has continued to surprise on the downside, allowing prospects of faster monetary easing; growth projected to recover gradually and remain moderate.
  - Macro prospects hinge on ambitious structural economic and fiscal reforms: address unsustainable expenditure mandates (including social security), consider more front-loaded fiscal deficit reduction, address infrastructure bottlenecks, simplify the tax code, and reduce barriers to trade.
- South Africa:
  - Growth softened and came to a near standstill in 2016 amid commodity price declines and perceptions of weakening governance and rising policy uncertainty.
  - Projected near-term recovery insufficient to keep pace with population growth.
  - Monetary policy can remain on hold in baseline unless inflation expectations rise or external financing becomes challenging.
  - Envisioned fiscal measures strike a balance between debt sustainability and safeguarding fragile recovery; if growth falters, additional measures—such as slower public sector wage increases and a moderate increase in consumption taxes—would be needed to stabilize the debt ratio.
  - With constraints on monetary and fiscal policy, urgent reforms in product and labor markets are needed to allow greater entry by new firms and reduce impediments to job creation.
- Russia:
  - Economy projected to continue nascent recovery in 2017.
  - Inflation expected to fall further toward the central bank’s inflation target over course of 2017, enabling gradual monetary policy easing with attention to external risks and credibility of the inflation-targeting regime.
  - Reestablishment of a three-year fiscal framework will help facilitate consolidation required by lower oil revenues.
  - Needed measures: better-targeted and more permanent reforms to the pension system, subsidies, and tax exemptions; adoption of a revised fiscal rule; improvements to financial supervision and regulation and a stronger resolution framework; diversification of the economy, accelerated institutional reforms, and improved business climate.

### Low-income developing countries: divergent prospects and policy priorities
- Divergence between commodity-exporting low-income countries and those with diversified export bases:
  - Commodity-exporting low-income developing countries hit by sharp realignment of global commodity prices since mid-2014: fiscal deficits remain wide, external positions weaker, debt rising, and depreciated currencies have sometimes led to higher inflation and increased external debt.
  - Most commodity exporters set to record positive growth in 2017, but medium-term prospects subdued.
  - Diversified low-income developing countries have recorded relatively strong growth and are expected to continue growing at a healthy rate, benefiting from lower oil bills outweighing drops in remittances and weaker demand from commodity exporters.
  - Many low-income countries have faced idiosyncratic shocks: conflicts and security disruptions (Afghanistan, Chad, South Sudan, Yemen, parts of Nigeria), natural disasters (Haiti, Ethiopia, Malawi), and lingering effects of Ebola (Guinea, Liberia, Sierra Leone).
- Policy guidance:
  - Commodity exporters: accelerate adjustment to structurally lower commodity prices with comprehensive policy sets; calibrate fiscal policy to contain debt accumulation while protecting priority capital expenditures and social spending; improve domestic revenue mobilization and rationalize spending; use concessional financing; consider monetary tightening to defend pegs or contain inflation; enhance financial sector regulation and supervision to manage foreign currency exposures.
  - Diversified low-income countries: balance spending for developmental and social needs with improving public debt sustainability; rebuild fiscal positions and foreign reserves while growth is strong; strengthen debt management to cope with capital flow volatility.
  - Long-term objectives aligned with the United Nations Sustainable Development Goals: create fiscal space by enhancing domestic resource mobilization, improve government spending efficiency and debt management, reorient fiscal spending to protect the vulnerable and address infrastructure gaps, and enhance financial sector resilience and inclusion.

### Multilateral policies: trade, taxation, financial stability, and longer-term challenges
- Trade:
  - Slower pace of new trade reforms and an uptick in protectionist measures have contributed to slowdown in global trade, though the estimated contribution is smaller than weakness in aggregate demand.
  - Rolling back temporary barriers introduced since the global financial crisis and reducing trade costs would support trade recovery.
  - Critical priorities: preserve the multilateral rules-based trading system; press ahead with an ambitious trade agenda; address tariff barriers in sectors where they remain high, such as agriculture; implement commitments under the Trade Facilitation Agreement, which went into effect in February 2017; advance trade reforms in services and "frontier" areas such as digital trade; improve cooperation in investment policies.
  - Further trade liberalization should be paired with domestic policies to support individuals and communities at risk of being left behind.
- International taxation:
  - Increased capital mobility has fueled international tax competition, making it harder to finance budgets without higher labor taxes or regressive consumption taxes.
  - National efforts to tackle tax evasion and avoidance need multilateral cooperation to prevent profit shifting across borders and sustain popular support for trade and investment flows.
- Global financial stability:
  - Continue efforts to strengthen resilience of the global financial system: recapitalize institutions, clean up balance sheets, ensure effective national and international banking resolution frameworks, and address risks from nonbank intermediaries.
  - A stronger global safety net can protect economies with robust fundamentals that may nonetheless be vulnerable to cross-border contagion and spillovers amid elevated downside risks.
  - Closer cross-border regulatory cooperation is required to limit the withdrawal of correspondent banking relationships that provide low-income countries access to the international payments system.
- Longer-term global challenges:
  - Multilateral cooperation indispensable for meeting the 2015 Sustainable Development Goals, providing financial support to vulnerable economies and fragile states, mitigating and adapting to climate change, and preventing spread of global epidemics.
  - Risks from noneconomic cross-border factors, such as the ongoing refugee crisis, underscore the need for globally funded vehicles to help exposed economies cope with strains.

*Source: text - introduction of quantitative and qualitative easing (PDF chapter/section).*

### CHAPTER 1

### CHAPTER 1

### Scenario Box 1 — Permanent U.S. Fiscal Expansions (G20MOD simulations)
- Purpose
  - Illustrate impact of two alternative U.S. fiscal expansions relative to a baseline with no change in U.S. fiscal policy using the IMF’s G20 Model (G20MOD).
  - Both expansions use identical instruments: reduced labor income taxes, reduced corporate income taxes, and increased infrastructure spending.
- Common assumptions
  - Fiscal expansion is debt financed for the first four years (2018–21).
  - U.S. monetary policy responds endogenously to the change in demand.
  - Monetary policy in Japan and the euro area accommodates positive increases in demand but has no conventional policy space to respond to negative developments.
  - Households and firms learn gradually about the changes in fiscal policy and their permanent nature.
  - After four years (2022) fiscal authority adjusts policy to stabilize the debt-to-GDP ratio.
  - In both cases, adjustments stabilize public-debt-to-GDP roughly 5 percentage points above prestimulus level.
- Key distinguishing assumptions between scenarios
  - Highly productive fiscal expansion (blue lines)
    - Increase in public infrastructure spending assumed to have a strong positive impact on output.
    - Cuts in labor income taxes assumed to be broad based.
    - Upon stabilization, fiscal authority partially cuts back initial infrastructure increase to maintain new higher public capital stock. Half of remaining required adjustment comes from reducing tax expenditures, and the other half from higher labor income taxes.
  - Less productive fiscal expansion (red lines)
    - Infrastructure spending assumed to be unproductive.
    - Tax cuts assumed to go mostly to wealthier households with a very low marginal propensity to spend.
    - Financial markets deliver faster normalization in the U.S. term premium: 25 basis points in 2018 and an additional 25 basis points in 2019.
    - Upon stabilization, increase in unproductive infrastructure spending is completely unwound and tax cuts to the wealthy are completely reversed; remaining adjustment via higher general labor income taxes.
- Results — growth, interest rates, exchange rate, and spillovers
  - U.S. Real GDP
    - Highly productive case: U.S. GDP rises notably, peaking at 1 percent above the no-policy-change case in 2021.
    - Less productive case: U.S. GDP rises by roughly half that amount by 2021.
  - Fiscal balances and debt
    - With smaller increase in U.S. output in the less productive case, the deficit and debt as a share of GDP both rise by more.
  - U.S. monetary policy and rates
    - In both cases, U.S. monetary policy tightens in response to higher demand and inflation.
    - Higher real U.S. interest rates lead to an appreciation of the U.S. dollar.
    - In the less productive case, the U.S. policy rate tightens by less, but faster normalization of the term premium and higher long-term interest rates leads to more upward pressure on the currency in the near term.
  - International spillovers
    - Highly productive case:
      - Other advanced economies benefit the most in the short term, with GDP roughly 0.2 percent higher (reflecting inclusion of Canada and Mexico).
      - Spillovers to emerging market economies are also positive in the short term, but modest.
    - Less productive case:
      - Short-term spillovers become negative for other advanced economies and for emerging market economies.
      - Reasons: smaller direct trade spillovers due to lower U.S. demand; faster normalization of term premiums tightens global financial conditions, onerous for advanced economies with limited conventional monetary policy space.
  - Long-term effects
    - Once fiscal policy is tightened to stabilize public debt, withdrawal of stimulus temporarily lowers U.S. GDP relative to 2021 in both cases.
    - Because capital income taxes are assumed permanently lower in both cases, real GDP subsequently recovers as firms continue investing to raise private capital stock.
    - In the highly productive expansion, permanently higher public capital stock raises private productivity and further increases return to private capital; U.S. output is permanently higher in the long term.
    - To maintain external stability, the U.S. dollar would need to depreciate given no change in the relative price of tradable and nontradable goods.
    - Spillovers to all economies outside the United States are small, but negative in the long term because permanently higher U.S. public debt raises global real interest rates; higher global interest rates permanently raise the cost of capital and more than offset the increase in the return to private capital from higher U.S. demand.
- Role of supply-side reforms and fiscal composition
  - Positive medium- and long-term effects on U.S. GDP arise from supply-side effects of some tax and expenditure changes (notably reduction in corporate income tax rates and increase in public investment in infrastructure) rather than simply from initial fiscal expansion.
  - Simulations show a similarly growth-friendly fiscal policy implemented in a deficit-neutral way (financed by a reduction in tax expenditures and lower government consumption) would lead to a higher long-term level of GDP.
    - Short term: GDP would be lower compared with the deficit-financed expansion; policy rates and long-term interest rates correspondingly lower; dollar would appreciate by less.
    - Medium/long term: no subsequent need for additional tightening of fiscal policy; lower medium-term debt implies long-term interest rates a bit lower — both factors support medium-term GDP.
- Scenario Table 1 — The Impact of Fiscal Measures on the Deficit (Percent of no-change-in-fiscal-measures case GDP)
  - Highly Productive Fiscal Measures (entries by year: 2017–2022)
    - Capital Income Taxes: 0 0.375 0.750 0.750 0.750 0.750
    - General Labor Income Taxes: 0 0.375 0.750 0.750 0.750 −0.330
    - Productive Infrastructure Spending: 0 0.250 0.500 0.500 0.500 0.150
    - Tax, Expenditures: 0 0 0 0 0 −0.320
    - Total Change in the Deficit: 0 1.000 2.000 2.000 2.000 0.200
  - Less Productive Fiscal Measures (entries by year: 2017–2022)
    - Capital Income Taxes: 0 0.375 0.750 0.750 0.750 0.750
    - Labor Income Taxes for the Wealthy: 0 0.375 0.750 0.750 0.750 0
    - General Labor Income Taxes: 0 0 0 0 0 −0.530
    - Unproductive Infrastructure Spending: 0 0.250 0.500 0.500 0.500 0
    - Total Change in the Deficit: 0 1.000 2.000 2.000 2.000 0.220
  - Source: IMF staff assumptions for the scenario analysis.

### Box 1.1 — Conflict, Growth, and Migration
- Recent trends and scope
  - Incidence of conflict defined as number of countries with at least 100 conflict-related deaths per 1 million people has risen in recent years from low levels in the early 2000s (Figure 1.1.1, panel 1).
  - Total annual number of conflict-related deaths has increased sharply in recent years, reflecting very deadly conflicts in Afghanistan, Iraq, and Syria (Figure 1.1.1, panel 2).
  - Nature and location of conflict changed over time: more interstate conflict between World War II and the 1990s; more internal civil war since the 1990s; location shifted from sub-Saharan Africa in the 1990s to broader Middle East region, especially since 2010.
  - Countries currently involved in conflict accounted for 1.0–2.5 percent of GDP in 2010, depending on precise threshold used to define incidence of conflict (Figure 1.1.2, panel 1).
- Economic costs and persistence
  - Conflict leads to long-lasting economic losses: reduced workforce, hampered labor productivity, permanent health damage, refugee flows, reduced schooling and human capital, lower investment, changes in household saving and consumption, and capital flight.
  - During 1989–2016, outbreaks of conflict are estimated to have reduced output per capita by a cumulative 18 percent over the subsequent 10 years, on average (Figure 1.1.3, panel 1).
  - Restricting analysis to state-based conflicts and using data for a longer period points to losses of about 5 percent after 10 years (Figure 1.1.3, panel 2).
  - Different conflict variable definitions yield:
    - If conflict fatalities (share of population killed): cumulative loss in output after 10 years about 5 percent.
    - If annual conflict incidence (dummy variable): cumulative loss about 7 percent (not shown in figures).
  - Econometric approach: local projection method of Jorda (2005) and Teulings and Zubanov (2014); results robust to various controls and to inclusion of preconflict GDP forecasts.
- Migration and refugee dynamics
  - Refugee populations tend to grow for many years after conflict begins, potentially placing significant burden on other economies.
  - Neighboring economies typically first to receive large influxes of refugees; if economic opportunities limited, refugees may move to advanced economies.
  - Refugee populations in advanced economies remain on the rise 10 years after the beginning of a conflict (Figure 1.1.3, panel 4).
- Quantitative representations (figures referenced)
  - Figure 1.1.1: Conflict-Related Fatalities and Number of Countries Affected by Conflict, panels for 1989–2016 and since World War II.
  - Figure 1.1.2: Global GDP Shares of Conflict-Affected Countries at Different Levels of Conflict Intensity (2002–05, 2006–09, 2010–16) and Preconflict GDP Forecast versus Actual (index, year before conflict = 100) for selected countries.
  - Figure 1.1.3: Impact of Conflict Onset on Economic Output after Conflict Onset (percent; years on x-axis) and Refugee Stocks after Conflict Onset with 95 percent confidence interval.
- Authors
  - The authors of this box are Natalija Novta and Evgenia Pugacheva.

### Irish national accounts revisions (July 12, 2016 Central Statistics Office revisions)
- Headline revisions
  - GDP growth in real terms for 2015 revised from preliminary 7.8 percent to 26.3 percent.
  - Gross national income (GNI) growth for 2015 revised from 5.7 percent to 18.7 percent.
  - Revisions to exports and imports resulted in an increase in net exports of more than €35 billion (about 17 percent of the preliminary 2015 GDP) reported in March 2016.
- Statistical conformity and drivers
  - Revisions conform to international standards: System of National Accounts (2008 SNA) and European System of Accounts (ESA 2010).
  - Main drivers:
    - Significant increase in external contract manufacturing activity attributable to Ireland.
    - Relocation and use of intellectual property products.
  - Contract manufacturing redomiciliation: value added from this production now recorded in Ireland; payments to manufacturer treated as importation of services; final output, once sold (exported), contributes to exports including intermediate inputs, license fees, other production costs, and profit margins.
  - Relocation of intellectual property products affects national accounts, balance of payments, and international investment position:
    - Net exports affected because (1) fees that firms located in Ireland charge foreign companies to manufacture patented products increase services exports, and (2) firms located in Ireland producing patented products no longer pay fees associated with relocated intellectual property products, reducing services imports.
    - GDP and GNI affected because increase in fixed assets implies an increase in estimates of depreciation.
  - Intellectual property product relocations recorded mostly as “other changes” in the international investment position—implying sharp downward revision to the net international investment position because transfer resulted in much larger intercompany debt in foreign direct investment liabilities.
  - If relocations had been recorded in the balance of payments, effects on GDP would have been the same, but Irish accounts would have shown:
    - An additional very large one-off increase in imports of services and a correspondingly large one-off current account deficit, along with a one-off increase in gross fixed capital formation in 2015.
- Context
  - Relocation of balance sheets (dominated by intellectual property) is not new, but the scale observed in these revisions was unprecedented.
- Author
  - The author of this box is Michael Stanger.

*Source: CHAPTER 1, text - CHAPTER 1, International Monetary Fund | April 2017.*

### 1. GDP and Gross National Income

### 1. GDP and Gross National Income

### Measurement challenges of Irish economic activity
- In 2015 the acquisition of foreign-owned intellectual property assets "added about €300 billion to Ireland’s capital stock and a similar amount to its net external liabilities."
- Activity attributable to goods for processing (contract manufacturing) also increased significantly; together these two factors "had a substantial impact on Ireland’s macroeconomic statistics, particularly given the small size of the economy."
- The acquisition of foreign-owned intellectual property assets adds to capital formation, and any subsequent revenue from licensing adds to Ireland’s GDP if licenses are charged; "this has not happened significantly to date."
- Growth of capital formation significantly increases standard measures of labor productivity and alters their relationship with domestically generated GDP and employment.
- Inclusion of contract manufacturing activity in statistical accounts increases output (exports), imports, GDP, and GNI, but leaves domestic employment mostly unchanged.
- GDP "is a measure of production and thus includes value added that accrues to foreign investors."
- GNI "is a measure of income, and Ireland’s GNI is significantly lower than its GDP because GNI does not include the income paid abroad or the retained earnings of foreign direct investors in Ireland."
- GNI does include retained earnings on foreign investment that is not direct; many corporate relocations to Ireland entail foreign investment that is not direct (individual owners fall short of the 10 percent threshold that classifies an investment as direct). In those cases, corporate entities are considered Irish, and their retained earnings are treated as Irish income, "even though retained earnings ultimately accrue to foreign shareholders through their impact on stock prices."
- For companies and products with substantial intellectual property content, retained earnings are typically sizable because they need to offset the relatively rapid depreciation of intellectual property capital.
- As a consequence of relocations, standard headline measures—domestic production, national income, domestic demand, and net exports—are less applicable to economic activity in Ireland. Conventional measures of fixed capital formation and domestic demand contain "significant components related to the nondomestic economy."
- Conclusion: "Additional measures to reflect the level of activity within the domestic economy are therefore required."

### Strategy to address measurement issues (Central Statistics Office response and recommendations)
- The Central Statistics Office of Ireland convened the Economic Statistics Review Group; the group finalized its report in December 2016, and in February 2017 the Central Statistics Office published its response to the report’s recommendations, including a timetable for implementation.
- GDP and GNI will remain the key international standard indicators; new analytical presentations and supplementary statistics will be made available.
- Implementation sequencing: "Annual aggregates will be developed first, followed by quarterly series where feasible and appropriate."
- Main recommendations to be implemented between mid-2017 and the end of 2018 include:
  - "A reliable indicator of the size of the economy that is relatively immune to relocations." The recommended indicator is an adjusted GNI that is an extension of the standard GNI and "takes into account the retained earnings of redomiciled firms and depreciation on foreign-owned domestic capital assets." Corresponding adjusted presentations of the balance of payments and international investment position data are also proposed.
  - "A standard set of structural macroeconomic indicators that better describe economic activity by multinational-company-dominated and domestic sectors." This includes a breakdown of the nonfinancial sector in the annual Institutional Sector Accounts into two broadly defined, foreign and domestic, subsectors, and the same detail for the entire system of national accounts, the balance of payments, and the international investment position.
  - "Additional detail on cross-border economic activities to allow for the monitoring of the domestic macroeconomic situation," providing increased detail on gross fixed capital formation, domestic demand, exports, and imports. An additional breakdown of the industrial production index is proposed.
  - "A number of initiatives to enhance the communication strategy to make it easier for users to understand major statistical releases."

### Ireland: Balance of Payments and International Investment Position (Table 1.2.1 key figures)
- Release 2015:Q4
  - Assets: 522.89 91.61 114.37 28.8
  - Liabilities: 311.59 0.7 –2.24 00.0
- Release 2016:Q1
  - Assets: 510.2 149.9 155.18 15.2
  - Liabilities: 342.7 169.8 283.1 795.6
- Revisions
  - Assets: 12.65 8.34 40.88 6.4
  - Liabilities: 31.27 9.22 285.33 95.6
- Sources: Central Statistics Office of Ireland (for data on balance of payments and international investment position); "Other Changes" derived residually.

### Broader context: selected macroeconomic snapshots from annex tables (extracts)
- Ireland (Annex Table snapshot)
  - Real GDP: 5.2 (2016), 3.5 (2017), 3.2 (2018)
  - Consumer Prices: –0.2 (2016), 0.9 (2017), 1.5 (2018)
  - Current Account Balance: 4.7 (2016), 4.7 (2017), 4.7 (2018) [percent of GDP]
  - Unemployment: 7.9 (2016), 6.5 (2017), 6.3 (2018) [percent]
- Note: Annex tables provide comparable indicators (Real GDP, Consumer Prices, Current Account Balance, Unemployment) for regions and countries; national definitions and reporting periods may differ.

### Commodity price developments (selected figures)
- IMF’s Primary Commodities Price Index "has increased by 15.5 percent since August 2016."
- Subcomponents since August 2016:
  - Energy: "rallied, by 21.1 percent"
  - Metals: "rallied, by 23.6 percent"
  - Food prices: "increased more modestly, by 4.9 percent"
  - Oil prices: "have continued to increase, by 21.2 percent"
  - Coal prices: "rallied, by 21.0 percent"
- OPEC agreement on November 30, 2016: members agreed to reduce crude oil output to "32.5 million barrels a day (mbd), effective January 2017 and for a duration of six months, extendable for another six months." That agreement "would suggest a cut of 1.2 mbd from production levels in October 2016."
- Notes on membership/exemptions: Libya and Nigeria are exempt; Indonesia "accounted for 0.75 mbd of production, has been suspended from OPEC."

*Source: World Economic Outlook: Gaining Momentum? — Chapter 1, "GDP and Gross National Income" and Box 1.2, International Monetary Fund | April 2017*

### 3. Brent Price Prospects

### 3. Brent Price Prospects

### Oil market developments and supply actions
- OPEC and non-OPEC production agreements in late 2016 included additional cuts amounting to about 0.6 mbd; Russia committed to reducing production by 0.3 mbd, with 10 other non-OPEC countries contributing the remainder.
- Saudi Arabia indicated it could cut production beyond its initial commitment to enhance credibility of the agreement.
- In response to these agreements, spot oil prices increased to more than $50 a barrel.
- Production data from the International Energy Agency (IEA) for January 2017 indicate that only a few OPEC members fully complied with the agreement, although Saudi Arabia has cut more than initially agreed on; Libya, exempt from the agreement, increased production.
- Oil demand grew at 1.6 mbd in 2016, lower than in 2015. The IEA expects demand growth to slow to 1.4 mbd in 2017—still above trend growth, estimated at 1.2 mbd.
- A significant cutback in production combined with fairly robust demand could move the oil market from surplus to deficit in the first half of 2017, reducing oil inventory levels.
- Rapid investment recovery in the U.S. shale sector could tip the market back into surplus as early as the second half of 2017; unlike conventional oil, U.S. shale can commence within a year of initial investment.

### Futures, baseline price assumptions, and risks
- Oil futures contracts point to stable prices of about $55 a barrel.
- Baseline assumptions for the IMF’s average petroleum spot prices, based on futures prices, suggest average annual prices of $55.2 a barrel in 2017—an increase of 28.9 percent from the 2016 average—and $55.1 a barrel in 2018.
- Futures response over a three-year horizon has been more muted, suggesting production agreements are expected to have a limited effect in the medium term.
- Uncertainty around baseline oil price assumptions remains, with risks described as balanced:
  - Upside risks: unscheduled outages and geopolitical events, especially in the Middle East.
  - Downside/mitigating factors: high inventory levels and a rapid response by shale production, which should prevent a sharp rise in prices in the near future.

### Natural gas and coal price movements and drivers
- The natural gas price index—an average for Europe, Japan, and the United States—has increased by 18.7 percent since August 2016.
  - Prices in Asia and the United States initially rose on expectations of strong winter demand, but a fairly mild winter led to subdued demand for gas-fired power generation and contained prices.
  - In Europe, prices rose 38.4 percent, reflecting higher oil prices and a cold winter.
  - Natural gas prices are expected to stay low because ample supply from the United States and Russia will meet strong natural gas demand growth—which is expected to exceed oil demand growth.
- The coal price index—an average of Australian and South African prices—has increased by 21.0 percent since August 2016.
  - Rally in coal prices reflects Chinese authorities’ effort to reduce coal mining capacity substantially as part of broader reform to restructure the economy.
  - To help soften rising prices, China has sought to relax restrictions on the number of days coal miners may work in a year.
  - Growing environmental and health concerns are expected to lead to a reduction in the share of coal in primary energy, accentuating excess capacity, especially in China.

### Metals: recent performance, drivers, and outlook
- Metal prices have increased by 23.6 percent since August 2016.
- Iron ore almost doubled in price in 2016 to $80 a metric ton.
- Drivers of metal price increases:
  - Rebound in metal consumption in China, which accounts for half of global demand, in response to policies supporting credit growth and construction activity.
  - Chinese authorities’ measures to address excess capacity in steel by cutting production of outdated factories, reducing pollution.
  - Increased use by Chinese steel mills of imported higher-grade iron ore.
  - Speculation over increased demand for cobalt has led spot prices to almost double since August 2016.
  - Announcement following the U.S. election of a $1 trillion infrastructure plan (over 10 years) provided a further boost to metal prices, though the global impact on world metal demand is likely modest (the United States accounted for only 8 percent of global refined copper demand in 2015 and 3 percent of iron ore demand in 2015).
- Supply-side factors:
  - Declining investment in, and closure of, high-cost and high-polluting mining operations have driven price increases in iron ore, nickel, tin, zinc, and copper.
  - Overall excess capacity will probably put downward pressure on prices in many base metals.
  - In January 2017, Indonesia relaxed its export ban on ores, partly offsetting supply drops caused by the Philippines’ closure of mines over environmental concerns.
- Outlook:
  - Most metal prices are expected to stay near current levels, except iron ore prices, which are expected to decline sharply.
  - The IMF metal price index is projected to decline from the current level, but its 2017 average is expected to increase by 23.2 percent from the average in 2016, reflecting the surge during late 2016.

*Source: International Monetary Fund, Special Feature: Commodity Market Developments and Forecasts, from "GAINING MOMENTUM? COMMODITY MARKET DEVELOPMENTS AND FORECASTS," April 2017.*

### 4.0 percent in 2018 from 2017. There are downside

### The Role of Technology and Unconventional Sources in the Global Oil Market

### Agricultural and Metal Price Developments
- Metals: projected to rise by 4.0 percent in 2018 from 2017; downside risks include waning policy support and real estate investment in China, faster rebalancing from investment to consumption in the medium term, or a disorderly adjustment in China’s corporate debt market.
- Agriculture index (food, beverages, agricultural raw materials): increased by 4.3 percent since August 2016.
- Commodity-specific movements since August 2016:
  - Wheat: increased by 15.2 percent since August 2016; reached an 11-year low in December 2016 but has since somewhat recovered.
  - Maize: increased but remains near historical lows.
  - Soybean: remained broadly unchanged.
  - Palm oil: climbed more than 36.7 percent throughout 2016 and increased 19 percent year over year.
  - Cocoa: annual price has fallen for the first time in five years due to favorable West African harvests.
- Market conditions: global stock-to-use ratios of wheat and maize remain significantly above the 10-year average, indicating well-supplied markets.

### Agricultural Price Projections and Risks
- Annual food price projections:
  - increase by 3.0 percent in 2017,
  - drop by 0.5 percent in 2018,
  - remain broadly unchanged thereafter.
- Upside risks: rising costs of energy and weather variability, including concerns about La Niña.
- Downside risks: China dismantling its price floor systems.

### Technology, Unconventional Oil, and Market Dynamics — Key Points
- Technological innovation is endogenous to oil prices: high oil prices prompted breakthroughs that led to unconventional oil sources (notably shale).
- Shale implications: will contribute to more limited and shorter production and price cycles.
- Innovation increases technically recoverable oil reserves, affecting expectations about future production and oil prices.
- Feedback mechanisms: lower oil prices reduce investment and production, but force efficiency gains that act as automatic stabilizers.

### What Are Unconventional Oil Sources?
- Current categories: oil sands, extra heavy oil, shale and tight oil, and ultradeepwater oil.
- Characteristics:
  - Oil sands: sands or partially consolidated sandstone saturated with bitumen; higher extraction, transportation, and refining costs; environmental concerns and safety regulations common.
  - Heavy and extra heavy oil: high viscosity, high density, high concentrations of nitrogen, oxygen, sulfur, and heavy metals; higher costs and environmental concerns.
  - Shale (tight) oil: light crude in low-permeability formations; developed using hydraulic fracturing and directional drilling; lower sunk costs and shorter lag from investment to production.
  - Deepwater: production at depths of more than 125 meters; ultradeepwater at 1,500 meters and above; ultradeepwater rigs can work beyond a depth of 3,000 meters and deliver long-lived steady streams of oil despite high fixed costs.

### Geography of Production and Reserves
- Concentration: production and proven reserves of unconventional sources are concentrated in a few countries.
- North America: highest concentration of economically recoverable proven reserves and production in unconventional sources (U.S. shale; Canadian oil sands).
- Central and South America: significant reserves and production (heavy and extra heavy oil; deepwater and ultradeepwater in Brazil, Colombia, Ecuador, Venezuela).
- Other regions: heavy oil in Europe; deepwater and ultradeepwater in the North Sea and West Africa.
- Middle East: highest concentration of conventional oil reserves and production but relatively low proven reserves and production in unconventional oil.
- Determinants: above-ground factors (openness to foreign investment, strength of property rights, regulatory environment, proximity to markets, infrastructure) matter alongside geology for proven reserves and production.

### Regulatory and Diffusion Issues for Shale
- U.S. regulatory history: expansion aided by a 2004 U.S. Environmental Protection Agency study on hydraulic fracturing and the Energy Policy Act of 2005 exemption of fracturing chemicals from Safe Drinking Water Act regulations.
- Global diffusion: shale deposits identified in Argentina, Australia, Canada, China, Mexico, Russia; except for Argentina and Canada, regulatory obstacles, technological challenges, and low oil prices have delayed extraction.
- Environmental concerns and tailoring of fracking to local geology have led some countries to ban shale exploration and production; global diffusion remains uncertain.

### Investment, Production, and Cost Dynamics
- Cyclical innovation: technological change in oil sector biased toward needs arising in periods of high prices; high prices in the 2000s fostered R&D increases.
- Research and development: historical comovement between oil prices and R&D/capex in major oil and service companies; current low-price environment reduces incentives for R&D in oil-recovery techniques.
- Capital and operational expenditure: historically tracked oil price developments; the 2000s saw an unprecedented increase in global capital expenditure for unconventional sources.
- Shale impact: shale oil requires lower sunk costs and shorter lags to production, contributing to shorter and more limited oil price cycles.
- Break-even and cost structure:
  - Break-even prices moved down in sync with oil prices during recent price drops due to operational efficiency gains.
  - Cost structure depends on technological improvements and “learning by doing,” which can reduce costs permanently, though depletion can outweigh technological progress over longer periods.

### Quantitative Highlights and Country Production (Table excerpts, 2016, Million barrels a day)
- United States total: 9.28
- Canada total: 3.28
- Brazil total: 2.39
- China total: 1.21
- Venezuela total: 1.18
- Angola total: 1.50
- Norway total: 1.39
- Nigeria total: 0.91
- Mexico total: 0.80
- Additional detail: in 2016, shale oil added 7.9 mbd in a market of 96 mbd—that is, 4.4 mbd in crude oil, 2.7 mbd in natural gas liquids, and 0.8 mbd in condensate.

*International Monetary Fund | April 2017*

### 1. Capital Expenditures

### 1. Capital Expenditures

### Key data, definitions, and measurement notes
- Capital expenditure includes exploration costs associated with seismic and drilling wildcats or appraisal wells to discover and delineate oil and gas fields, and all development costs related to facilities and drilling of wells.
- Operational expenditure includes operational expenses directly related to oil and gas activities.
- Costs are estimated at asset level and calibrated against company reported values.
- APSP = average petroleum spot price–average of U.K. Brent, Dubai, and West Texas Intermediate, equally weighted.
- Deepwater is defined at 125–1,500 meters. Ultradeepwater is defined at 1,500 meters and above.
- When deepwater (or ultradeepwater) production was also categorized as heavy (or extra heavy) oil, the production was counted once, as deepwater (or ultradeepwater).
- Oil refers to crude oil, condensate, and natural gas liquids.
- The breakeven price is the Brent oil price at which net present value equals zero, considering all future cash flows using a real discount rate of 7.5 percent.
- Total world production in 2016 was estimated at 96.5 mbd (million barrels a day).

### Observed patterns and sectoral cost structure
- Shale (tight) oil displayed extraordinary resilience to the drop in oil prices, explained by important efficiency gains and learning-by-doing from an investment cycle.
- Some efficiency gains in shale cannot be sustained under an expansion of oil production; the cost of capital is expected to increase as U.S. interest rates rise.
- Oil sand production has shown continued high growth rates but is subject to high decommissioning costs; lower investment in exploring new fields is expected to affect oil sands production over time.
- Deepwater and ultradeepwater oil production has been subject to active upgrading, making it somewhat resilient, but lower investment in new fields will tend to affect deepwater and ultradeepwater oil in the future with regional heterogeneity.

### Cost and breakeven price information (from figures)
- Figure 1.SF.6 cost and breakeven markers (U.S. dollars a barrel) include the following category values as shown: 29, 43, 49, 53, 54, 55, 57, 62, 74.
- A scenario note: under no cost deflation, the oil price level required to keep shale production constant is higher than $80 a barrel. With cost deflation of about 40 percent, the required price level is only $40 a barrel.
- Figure 1.SF.7 shale-well drilling example: At $60/barrel, approximately 8,000 shale wells have to be drilled, with 10 percent cost deflation, to keep production flat.
- Figure 1.SF.8 and text emphasize substantial uncertainty in forecasting unconventional production relative to conventional production.

### Market balances, projections, and scenarios
- The negotiated reduction in oil production by 1.8 mbd for six months is expected, in principle, to help rebalance the market by the end of 2017, eliminating an excess supply currently estimated to be a little less than 1 mbd.
- Annual oil demand growth, commonly projected at about 1.2 mbd, will be met by unconventional sources over the next few years, mainly through resources under development for deepwater and ultradeepwater oil, oil sands, and heavy and extra heavy oil.
- In the absence of shale, depletion forces and the legacy of low investment would start to push prices up significantly after a few years.
- Shale supply response: moderate price increases will stimulate shale production, helping to dampen sharp upward swings in oil prices; over the medium term, higher prices will reactivate technical improvements in unconventional oil recovery and potentially set off another price cycle.

### Uncertainty and technological adoption
- The development of unconventional sources is inherently uncertain, driven by unpredictable technological improvements and their adoption, including the extent of learning and spatial diffusion.
- The rising importance of unconventional sources is changing the dynamic response of production to prices and increasing medium-term uncertainty.

### Policy-relevant implications and recommendations
- Emerging market and developing economies face a potentially less supportive external environment going forward and should:
  - Strengthen their institutional frameworks.
  - Protect trade integration.
  - Permit exchange rate flexibility.
  - Contain vulnerabilities arising from high current account deficits and external borrowing.
  - Contain vulnerabilities arising from large public debt.

*Source: IMF staff text from "1. Capital Expenditures" (World Economic Outlook: Gaining Momentum?, April 2017).*

### Introduction

### Introduction

### Background: a more complicated external environment
- After a remarkable period of synchronized acceleration in the early 2000s and broad resilience immediately following the global financial crisis, growth across emerging market and developing economies in recent years displays heterogeneity—a mix of tapering, standstills, reversals, and continued strength in some cases.
- This change has taken place against a backdrop of fading external tailwinds, including waning potential growth in advanced economies, slowdown and rebalancing in China, and a shift in the commodity cycle that has affected commodity exporters.
- Additional external risks include a risk of protectionism in advanced economies and tighter financial conditions as U.S. monetary policy normalizes.
- These developments make for a more challenging external environment for emerging market and developing economies going forward.

### Research focus and questions
- The chapter studies how country-specific external conditions affect emerging market and developing economies’ medium-term growth prospects (that is, over five-year horizons that smooth the influence of business cycle fluctuations) and their likelihood of experiencing persistent acceleration and reversal episodes.
- It explores how domestic policies and structural attributes influence the impact of external conditions on the propensity to experience these episodes.
- Main questions examined:
  - How do country-specific external demand conditions, external financial conditions, and terms of trade influence growth patterns, the likelihood of accelerations or reversals, and the pace of narrowing income gaps vis-à-vis advanced economies? As EMDEs have become more integrated into the global economy, have external factors become more important in shaping their growth patterns over time?
  - Which domestic policies and structural attributes can help EMDEs get the most out of external conditions?
  - What does the current constellation of external conditions imply for EMDEs’ medium-term growth prospects and their ability to continue to contribute significantly to global growth?

### Main findings
- Country-specific external conditions have a significant effect on medium-term growth of emerging market and developing economies.
  - Variation at the country level in external conditions, as well as global factors that affect all economies in a common manner during particular intervals, matter for medium-term growth outcomes of individual EMDEs.
- Country-specific external conditions also help explain the occurrence of growth accelerations and reversals—episodes that appear to have persistent effects on growth outcomes in EMDEs and their relative income gaps vis-à-vis advanced economies.
- The importance of country-specific external conditions for EMDEs’ medium-term growth has increased over time, particularly in the case of external financial conditions.
  - Their contribution to medium-term growth has increased by about ½ percentage point—or one-third of the increase in average per capita income growth—between the 1995–2004 and 2005–14 periods.
  - While the contribution of external demand conditions as a whole appears to have remained broadly stable over this period, demand among emerging market and developing economies has played an increasingly powerful role.
- Certain domestic policy settings and structural attributes can to some extent help offset a diminishing growth impulse from less supportive external conditions.
  - Higher-quality legal systems and stronger protection of property rights are associated with better medium-term growth outcomes.
  - Sound monetary frameworks, financial depth, and exchange rate flexibility also enhance medium-term growth.
  - Trade integration, exchange rate flexibility, and strong institutions help EMDEs enhance the growth impulse from external conditions either by increasing the likelihood of accelerations or by decreasing that of reversals.

### Scope and caveats
- The analysis focuses specifically on the impact of the external environment on EMDEs’ medium-term growth in income per capita.
- The external environment can also influence other important aspects not considered in this chapter:
  - External demand and financial shocks have a quantitatively significant impact on short-term growth fluctuations in EMDEs.
  - Exposure to short-term speculative capital flows can impose costs in the form of higher volatility.
  - Integration into the global trading system affects the way rewards of economic growth are divided across domestic factors of production; participation in global value chains may have contributed to lower labor income shares in EMDEs.

### Emerging market and developing economy growth performance over time
- EMDEs’ contribution to global growth of output and consumption increased rapidly in recent decades and became increasingly relevant for the global economy.
  - During 2000–08, EMDEs, on average, accounted for 70 percent of global growth in output and consumption in purchasing-power-parity terms, nearly double their contribution during the 1980s.
  - After the global financial crisis, with advanced economies experiencing a slow recovery, EMDEs’ contribution to global growth rose to about 80 percent of output growth and 85 percent of consumption growth.
  - In market exchange-rate terms, EMDEs accounted for close to 70 percent of global output growth and just over 70 percent of global consumption growth during 2010–15.
- Despite EMDEs’ increasing overall importance, income levels of individual countries within the group remain relatively low vis-à-vis those of advanced economies.
  - In 90 percent of EMDEs, current real income per capita (converted at purchasing-power-parity exchange rates) is less than half what it is in the United States.
  - In 85 percent of EMDEs, real income per worker is less than half that in the United States.
- Large gaps in income per worker vis-à-vis advanced economies suggest there may still be significant room for catch-up growth in EMDEs, though catch-up is not automatic.
  - Historical evidence shows episodes of accelerations and reversals in growth across EMDEs, and some bottom-quintile groups saw median relative income decline over four decades while others in higher quintiles saw increases.
  - Some EMDEs may be close to their own steady-state levels and unlikely to experience further catch-up growth; in recent years some EMDEs have experienced a protracted slowdown in labor productivity growth.

*Source: IMF staff, “ROADS LESS TRAVELED: GROWTH IN EMERGING MARKET AND DEVELOPING ECONOMIES IN A COMPLICATED EXTERNAL ENVIRONMENT,” World Economic Outlook, April 2017.*

### CHAPTER 2

### CHAPTER 2

### How Important Are External Conditions?
- The chapter explores the role of external conditions in accounting for episodic accelerations and reversals in emerging market and developing economies’ (EMDEs’) growth, noting that income gaps vis-à-vis the United States have both narrowed and widened across decades.
- Narrowing of EMDEs’ relative income gap with the United States during the 2000s and 2010s reflected exceptional tailwinds and synchronized accelerations, not "convergence from above," since real GDP per capita in the United States did not decline in absolute terms except during the global financial crisis.
- The analysis builds on prior research documenting the importance of external demand and terms of trade for medium-term growth and of trade integration for growth accelerations.

### Country-Specific External Conditions Measures
- The chapter focuses on three sets of external conditions: external demand conditions, external financial conditions, and terms of trade, and constructs country-specific metrics intended to be largely exogenous to each economy.
- Country-specific external demand conditions:
  - Measured by the export-weighted growth rate of domestic absorption of trading partners (Arora and Vamvakidis (2005) and IMF (2014)).
  - Decomposed by three groups of trading partners: China, other EMDEs (excluding China), and advanced economies.
- Country-specific external financial conditions:
  - Proxied by a quantity-based measure of capital flows to peer economies (other EMDEs within the same region) as a share of their aggregate GDP (constructed to be exogenous to each country along the lines of Blanchard, Adler, and de Carvalho Filho 2015).
  - A quantity-based metric is used to capture fluctuations in availability of diverse financial flows ranging from direct investment to cross-border bank lending.
- Country-specific changes in the terms of trade:
  - Based on international commodity prices as in Gruss 2014 and Chapter 2 of the October 2015 WEO.
  - The commodity terms of trade index is weighted by the share of net exports of each commodity in GDP, with predetermined weights so movements reflect exogenous changes in international prices.
- Cross-correlations and idiosyncratic variation:
  - The cross-correlation between the three country-specific measures of external conditions is low (Annex Table 2.1.3), indicating separate influences.
  - Country-specific measures often deviate considerably from corresponding global variables, showing substantial idiosyncratic variation (Annex Figure 2.1.1).
  - External financial conditions show a strong regional common factor, yet substantial variability remains when restricting peers to the same geographical region.
  - Correlation of changes in commodity terms of trade with oil prices or aggregate commodity prices varies substantially across countries.

### Establishing the Importance of External Conditions
- Empirical approach:
  - Follows Arora and Vamvakidis (2005), Calderón, Loayza, and Schmidt-Hebbel (2006), and Box 4.1 in Chapter 4 of the April 2014 WEO.
  - Estimates a standard growth regression over 1970–2014 for more than 80 EMDEs (Annex 2.3).
  - Dependent variable: growth rate of GDP per capita in purchasing-power-parity terms averaged over nonoverlapping five-year windows.
  - Explanatory variables: the three country-specific external conditions measures, country and time fixed effects, initial real income per capita, and a set of domestic variables associated with medium-term growth.
  - Time fixed effects capture unobservable common factors; specifications allow unobserved country fixed effects.
  - Robustness: results robust to excluding key large EMDEs, using alternative external measures less likely affected by domestic growth, and instrumenting some external variables with exogenous variables (Annex 2.3).
- Main estimated effects (whole sample, 1970–2014; coefficients statistically significant at the 10 percent level):
  - A 1 percentage point increase in the growth rate of domestic absorption in trading partners is associated with a 0.4 percentage point increase in medium-term growth (about one-fifth of the average annual growth rate of GDP per capita in the sample).
  - A 1 percentage point increase in the ratio of capital flows to GDP of EMDEs within the region raises medium-term growth by 0.2 percentage point.
  - A 1 percentage point increase in commodity terms of trade increases medium-term growth by almost ½ percentage point.
- Interpretation:
  - External demand may deliver persistent productivity gains from larger market size via trade.
  - Larger volumes of financial inflows can ease credit rationing and reduce borrowing costs, supporting growth.
  - Commodity terms-of-trade windfalls comove with actual and potential output.

### Has the Role of External Conditions Evolved across Groups of Economies and over Time?
- Sample sensitivity:
  - Re-estimations excluding China, and excluding all G20 members in the sample (Argentina, Brazil, China, India, Indonesia, Korea, Mexico, Russia, Saudi Arabia, South Africa, Turkey) yield coefficients very similar to the overall sample (Annex Table 2.3.2), suggesting large economies do not drive the overall results.
- Excluding smallest economies:
  - A reduced sample that excludes the smallest economies (collectively accounting for less than 5 percent of EMDE aggregate GDP) shows:
    - The coefficient on terms of trade about twice as large and strongly significant.
    - The coefficient on external financial conditions similar to the full sample estimate.
    - The coefficient on external demand conditions smaller and statistically insignificant.
- Evolution over time (rolling regressions over 20-year horizons with four nonoverlapping five-year windows):
  - Coefficients generally increase over time as countries become more integrated into the global economy (Figure 2.5, panel 2).
  - The elasticity with respect to external demand is almost four times as large over 1995–2014 compared with 1980–99.
  - The elasticity with respect to commodity terms of trade is more than twice as large over 1995–2014 compared with 1980–99.
  - The elasticity with respect to external financial conditions varies much less over time.

### Contribution of Country-Specific External Conditions to Per Capita Income Growth
- Full-sample average contributions (1975–2014):
  - The three external conditions collectively contributed, on average, almost 2 percentage points to income per capita growth over 1975–2014 (Figure 2.6, panel 1).
  - Contribution increased from about 1.7 percentage points over 1975–94 to about 2⅓ percentage points during the past two decades, accounting for more than half of medium-term growth, on average, across EMDEs during the latter period.
- Regional patterns:
  - External conditions have been very important for growth in Latin America and the Caribbean; the Middle East, North Africa, Afghanistan, and Pakistan; and sub-Saharan Africa.
  - For Asia and European EMDEs, domestic and unaccounted-for factors play a relatively larger role.

*International Monetary Fund | April 2017*

### CHAPTER 2

### CHAPTER 2 — ROaDs LEss TRavELED: GROWTh IN EMERGING MaRKET aND DEvELOpING ECONOMIEs IN a COMpLICaTED ExTERNaL ENvIRONMENT

### Role of External Conditions in Medium-Term Growth
- Financial conditions, proxied by the intensity of gross capital inflows, have become increasingly important over time:
  - Their contribution to medium-term growth has increased by about ½ percentage point between the 1995–2004 and 2005–14 periods.
  - This increase represents one-third of the increase in average income per capita growth over that interval.
  - Financial conditions account for about half of the contribution from external factors since 2005—up from about one-third during 1995–2004.
- Changes in external demand composition have shifted importance toward China and other EMDEs:
  - China’s domestic absorption from 2000 onward has become increasingly important in accounting for growth in other emerging market and developing economies.
  - The combined demand from China and other EMDEs accounts for more than 80 percent of the contribution of external demand to GDP per capita growth in other EMDEs (up from 36 percent in the late 1990s).
- Commodity terms of trade (CTOT) effects are heterogeneous:
  - For the average economy in the sample the contribution of CTOT to medium-term growth appears relatively small.
  - For commodity exporters the contribution of CTOT to annual GDP per capita growth fluctuates from about 1 percentage point (around the late 1970s oil price shock and the early 2000s commodity boom) to –0.6 percentage point in the mid-1980s.
- Joint variance explained by the three external conditions:
  - Over the whole sample, commodity terms of trade account for almost 40 percent of the variance attributable to the three external factors.
  - External demand accounts for about 35 percent of that variance.
  - External financial conditions account for the remaining 25 percent.
  - The share attributable to CTOT among all three external variables was as large as 80 percent in 1975–80 but only about 10 percent in 1990–94.
- Overall conclusion:
  - Country-specific external conditions are important drivers of medium-term growth in EMDEs, and their importance has increased as economies opened to trade and integrated financially into international capital markets.

### Common Factors and External Financial Conditions
- Time fixed effects capture other common factors, including external conditions common across economies:
  - The contribution of these other common factors was relatively stable during 1975–99, but increased sharply since the early 2000s.
  - Comparing estimated common factors with global activity and financial variables suggests the overall contribution of external conditions—and particularly external financial conditions—to medium-term growth over the past 15 years may be larger than captured by country-specific external variables alone.
- Possible drivers of the increased common-factor contribution since 2000:
  - A synchronized increase of gross capital inflows to EMDEs.
  - Changing intra-EMDE trade linkages (including an increasing share of value added from EMDEs absorbed by China’s final demand during the 2000s that outpaced what could be explained by China’s GDP growth).
  - Increased EMDE participation in global value chains since the mid-1990s, affecting resource use efficiency and productivity growth.

### Identification and Characteristics of Growth Episodes
- Definitions and statistical thresholds used to identify episodes (five-year intervals):
  - Growth acceleration episode criteria:
    - Trend growth rate of real GDP per capita during the period is at least 3.5 percent a year.
    - Trend growth increases by at least 2 percentage points relative to the preceding interval.
    - The level of real GDP per capita at the end of the episode is at least as large as the maximum level recorded prior to onset (to exclude rebounds from collapses).
    - Accelerations followed by a reversal within three years of the episode’s end, or associated with a banking crisis starting three years before or after the episode’s end, are labeled nonpersistent.
  - Growth reversal episode criteria:
    - A discrete drop in trend growth of at least 2 percentage points relative to the preceding five-year interval.
    - The five-year episode’s average level of real GDP per capita is lower than the average during the immediately preceding five-year period.
- Episode counts and classification (1970–2014):
  - Total growth acceleration episodes: 127.
    - Persistent accelerations: 95.
    - Nonpersistent accelerations: 32.
      - Of the 32 nonpersistent accelerations, 12 are associated with subsequent reversals, 18 with banking crises, and 2 with both.
  - Growth reversal episodes identified: 125.
- Temporal and regional patterns:
  - Accelerations picked up in the 2000s and skewed increasingly toward persistent accelerations in recent decades.
  - Reversals were numerous in the 1970s and 1980s (notably affecting oil-importing EMDEs and LAC) but have declined since then.
  - Accelerations have been relatively steady in Asia; reversals are more concentrated in MENAP, LAC, and SSA. Asia and Europe have seen fewer reversals.

### Magnitude and Persistence of Episode Effects
- Typical cumulative effects on real income per capita:
  - Persistent accelerations are associated with increases in real income per capita typically ranging from 15–40 percent above the starting level before the episode.
  - Reversals typically reduce real income per capita by 5–30 percent relative to the initial starting level, with declines as large as 50 percent in extreme cases (e.g., Sierra Leone in the mid-1990s).
- Persistence over time:
  - Persistent accelerations are associated with permanent increases in income levels: during the two decades after the onset of a persistent acceleration, the median level of income per capita increases nearly twice as much as the median level for economies that do not experience accelerations.
  - Nonpersistent accelerations show similar growth in the first five years but slower increases thereafter, leading to lower levels eight years after onset compared with persistent accelerations.
  - Reversals have long-lasting negative effects, with the level of real GDP per capita not returning to the start-of-episode level until about 15 years after the start of the reversal.
- Relationship with long-term growth:
  - Economies with larger cumulative income gains during persistent accelerations tend to achieve higher long-term average growth rates.
  - Economies with larger cumulative income losses during reversals tend to have lower long-term average growth rates.
- Comparative magnitude:
  - Median annual growth rate during persistent acceleration episodes: about 5.5 percent.
  - Median annual growth rate for comparator economies not in an episode over the same period: 1.7 percent.

*Source: CHAPTER 2, text - CHAPTER 2 (World Economic Outlook: Gaining Momentum?, International Monetary Fund | April 2017).*

### 1. Economies Experiencing Persistent Accelerations and

### 1. Economies Experiencing Persistent Accelerations and Benchmark Economies

### Event-analysis summary: growth episodes, medians, and external conditions
- The median growth rate during reversals is –3 percent (compared with 2.6 percent for comparators over the same period).
- For persistent acceleration episodes:
  - The median of trading partner growth is "just above half a percentage point higher" than the median trading partner growth for comparator economies not in an episode.
  - External financing—the gross capital flow into the region—is about 1.5 percentage points higher than for comparator economies.
  - The median change in commodity terms of trade is –0.2 percent for persistent accelerations versus about –0.1 percent for the comparator countries (full sample includes both commodity importers and exporters).
  - For commodity exporters only, the median change in terms of trade is 0.9 percent for those experiencing persistent accelerations and 0.1 percent for comparator commodity exporters.
- For reversal episodes:
  - Trading partner growth is almost 0.7 percentage point lower than for nonepisodes spanning the same time interval.
  - Capital flows to the region for reversal episodes are roughly 0.7 percentage point lower compared with nonepisode countries over the same period.
  - The median change in terms of trade for reversals is –0.10 percent versus –0.08 percent for nonepisode countries (no statistically significant difference for full sample).
  - Among commodity exporters in reversal episodes, terms of trade decline by about 0.75 percentage point versus an increase of about 0.3 percentage point for commodity exporters that did not experience a reversal.

### Interpretation
- Differences in external conditions between economies that experience growth episodes and those that do not suggest external conditions may play a relevant role in the occurrence and persistence of growth episodes.
- Commodity terms-of-trade changes matter more for commodity exporters; terms-of-trade windfalls can trigger nonpersistent accelerations.

### Methodological note (as used in the analysis)
- Each external variable is measured as the average between t + 1 and t + 5, where t corresponds to the onset of the episode.
- Growth episodes are identified according to the criteria described in Annex 2.4.
- Significance annotations: ***, **, and * denote significance of an equality test of medians at the 1, 5, and 10 percent level, respectively.

---

### 2. The Tipping Point: Marginal effects of external conditions (logit regressions)

### Key marginal-effect estimates (external conditions evaluated at their means)
- Accelerations (persistent):
  - A 1 percentage point increase in trading partner demand raises the probability of acceleration by 3.9 percentage points.
  - Compared with the unconditional probability, this represents a near-doubling—to 9.7 percent—of the probability of acceleration.
  - A 1 percentage point of GDP increase in regional capital flows raises the probability of persistent acceleration by 2.6 percentage points.
  - An improvement in the terms of trade is not significantly associated with persistent accelerations in the full EMDE sample, with two exceptions:
    - For commodity exporters, an increase in the terms of trade is significantly associated with an increase in the likelihood of persistent accelerations.
    - For the subset of 32 nonpersistent accelerations, an increase in the terms of trade is significantly associated with the occurrence of such episodes.
- Reversals:
  - A 1 percentage point increase in external demand lowers the probability of a reversal by 4 percentage points (about 50 percent of the unconditional probability).
  - A 1 percentage point of GDP increase in capital flows to the region is associated with a 2.4 percentage point decrease in the probability of a reversal.
  - The change in terms of trade is associated with a statistically significant reduction in the likelihood of reversals of 0.6 percentage point.

### Robustness and specification
- Estimates are from a logistic regression with a dummy for the identified episodes as dependent variable and including country fixed effects and the three external conditions variables.
- Results are robust to inclusion of additional controls (see Annex 2.5 and Annex 2.6 references in source).
- Vertical lines in the plotted results denote 90 percent confidence intervals.
- CTOT = commodity terms of trade.

---

### 3. The role of domestic policies and structural attributes

### Four broad categories of domestic attributes examined
- Degree of de jure trade and financial integration, and domestic financial depth (proxy for capacity to intermediate cross-border capital flows).
- Initial conditions at onset of episode: level of external debt and the current account balance.
- Macroeconomic policy framework: exchange rate regime, extent of monetary stability, level of public debt.
- Structural factors and institutions: quality of governance, legal and regulatory environment, availability of public services, level of education.

### Empirical findings on domestic attributes (comparisons of episodes vs nonepisodes)
- Economies experiencing accelerations have:
  - A larger number of free trade agreements than comparator economies not experiencing accelerations.
  - Higher financial depth (measured as the ratio of bank assets to GDP) than comparators.
- Economies experiencing reversals have:
  - A smaller number of free trade agreements than comparator economies not experiencing reversals.
  - Lower financial depth than comparators.

### Results from regressions incorporating domestic attributes (Annex 2.6)
- Stronger institutions (proxied by higher-quality legal systems and better protection of property rights) are significantly associated with a higher likelihood of experiencing persistent acceleration episodes.
- The likelihood of experiencing growth reversal episodes significantly decreases with the extent of exchange rate flexibility.
- A sound monetary framework and greater domestic financial depth are significantly associated with:
  - A higher likelihood of persistent acceleration episodes.
  - A lower likelihood of growth reversal episodes.
- Trade and financial openness and initial conditions, by themselves, are not found to significantly affect the probability of experiencing a sustained shift in growth—though they may shape how external conditions influence the occurrence of episodes.

### How domestic attributes mediate external impacts
- The analysis finds that several domestic attributes influence the marginal effect of external conditions on the likelihood of accelerations and reversals:
  - More integrated economies may be more sensitive to external conditions.
  - Better policy frameworks and institutional quality can amplify the persistence of favorable responses to improved external conditions and mitigate the probability of persistent reversals.
  - Prudent fiscal policy and flexible exchange rate regimes can help buffer adverse external shocks and reduce the probability of persistent reversals.

---

*Source: IMF staff calculations; World Economic Outlook: Gaining Momentum? — Chapter 2, April 2017*

### 1. Trade Agreements

### 1. Trade Agreements

### Key findings on integration and domestic absorptive capacity
- Deeper de jure trade integration, proxied by the number of trading partners with which a country has a trade agreement, increases the likelihood that supportive external conditions lead to growth accelerations in emerging market and developing economies.
- When the number of partners with which an economy has free trade agreements increases from the 25th to the 75th percentile in the sample, a 1 percentage point increase in external demand raises the probability of an acceleration by 3 additional percentage points.
- Financial development amplifies benefits from favorable external financial conditions: an increase in capital inflows to the region of 1 percentage point of GDP raises the probability of accelerations by 6.6 percent in economies at the 75th percentile of financial development compared with 4.5 percent in economies at the 25th percentile; the difference is statistically significant.
- Deeper financial systems reduce, for a given impulse from external financial conditions, the probability of reversals by only ⅓ percentage point.
- Sound credit growth is associated with stronger outcomes under favorable external financial conditions:
  - The probability of a persistent acceleration when external financial conditions are supportive is about 7 percentage points higher when domestic credit has been growing at a healthy pace as opposed to under credit-boom conditions.
  - The marginal effect of external financial conditions on reversals improves (the probability of the episode decreases) by 2⅓ percentage points for economies that avoid excessive credit growth.
- Capital account openness:
  - Enhances the supportive role of external financial conditions in avoiding reversals: in more open economies, favorable external financial conditions lower the probability of reversals 2½ percentage points more than under restrictive capital account settings.
  - The probability of an acceleration increases less for economies with more open capital accounts—although the change in the marginal effect is small and not statistically significant.

### Measurement and modeling notes (as used for these findings)
- Domestic attributes are measured as the moving average of the variable during the three years preceding the onset of the episode (average between t – 3 and t – 1).
- The exercise evaluates how shifting each domestic attribute from its 25th percentile (low quality) to its 75th percentile (high quality) changes the marginal effect of external conditions evaluated at their medians.
- Financial depth proxied by the ratio of bank assets to GDP; capital account openness based on Quinn (1997) measure; de jure trade integration from the Design of Trade Agreements database.

### Initial conditions and external imbalances
- A small current account deficit significantly increases the marginal effect of external financial conditions on the probability of accelerations by ¾ percentage point, while it has a negligible and statistically insignificant impact on the probability of reversals.
- The marginal effect of better external demand conditions on the likelihood of an acceleration improves by 1 percentage point when the initial current account deficit is small.
- The effect of demand conditions on the probability of reversals decreases by 1½ percentage points when the initial current account deficit is small.
- Lower external debt increases the likelihood of accelerations when external demand conditions, terms of trade, or external financial conditions improve—by about 1½ percentage points, 1 percentage point, and ⅓ percentage point, respectively.
- Lower external debt also increases the extent to which improvements in terms of trade reduce the probability of reversals.

### Policy frameworks that moderate external impulses
- Exchange rate flexibility:
  - The marginal effect of external demand conditions on the likelihood of episodes of sustained growth improves by 3 percentage points with exchange rate flexibility.
  - The effect of external financial conditions on the probability of experiencing a period of sustained growth is about 1¼ percentage points larger under a more flexible exchange rate regime.
  - The probability of a reversal decreases further and significantly—by about 2 percentage points—under a more flexible exchange rate regime.
- Fiscal discipline:
  - Prudent fiscal policy, proxied by the level of public debt to GDP, improves the impact of external demand conditions: the marginal effect of external demand on the likelihood of persistent accelerations improves by about 1.8 percentage points when public debt is low.

### Structural characteristics
- Quality of regulation:
  - The marginal effect of external demand on accelerations increases significantly—by 8 percentage points—when the quality of regulation improves.
- Legal system and property rights:
  - An improvement in the quality of the legal system and property rights increases the marginal effect of external demand on accelerations by 9 percentage points and decreases the probability of reversals by 3 percentage points.
- Overall: improvements in regulation, legal institutions, exchange rate flexibility, and containment of external and public debt are associated with better growth outturns for a given impulse from external conditions.

### External environment outlook and implications for EMDEs
- The external environment for emerging market and developing economies has become more complicated; some conditions may be less supportive and others are highly uncertain.
- External demand:
  - Waning potential output growth in advanced economies: WEO projections for advanced economy potential output growth reduced from close to 2 percent (October 2014 WEO) to just over 1½ percent (October 2016 WEO).
  - Risk of protectionism and less favorable views of integration may weaken external demand.
  - Growth in external demand, on average, is expected to be weaker during 2017–22 than in the past.
- External financial conditions:
  - Expected to gradually tighten as U.S. monetary policy normalizes, but a search for yield may continue to bring capital to some EMDEs; investors likely to discriminate based on fundamentals.
- Commodity terms of trade may improve for some economies as commodity prices recover, but remain subdued compared with past boom years.
- Net implication: EMDEs should expect a weaker growth impulse from external conditions than in the post-2000 period, but domestic policies and structural attributes can mediate this effect.

### Policy recommendations and strategic priorities
- Strengthen institutional frameworks and structural attributes, including:
  - Protecting trade integration (expand de jure trade agreements and openness).
  - Permitting exchange rate flexibility to improve allocation and absorb external demand and financial shocks.
  - Ensuring financial systems are deep, developed, and supervised to channel external financing productively while avoiding excessive credit growth.
  - Maintaining fiscal discipline to keep public debt at low levels.
  - Containing vulnerabilities associated with large current account deficits and high external debt.
  - Improving the quality of regulation and the legal system and property rights protection.
- These policies and reforms can help EMDEs extract more favorable growth outcomes from weaker external impulses; in some cases, improvements (for example, opening to trade or allowing more exchange rate flexibility) can almost entirely offset a 1 percentage point weaker growth of trading partners’ demand.

*Source: IMF staff calculations (World Economic Outlook: Gaining Momentum?, April 2017).*

### CHAPTER 2

### CHAPTER 2 — ROaDs LEss TRavELED: GROWTh IN EMERGING MaRKET aND DEvELOpING ECONOMIEs IN a COMpLICaTED ExTERNaL ENvIRONMENT

### Box 2.1 — Within-Country Trends in Income per Capita: The Cases of Brazil, Russia, India, China, and South Africa
- Purpose and data:
  - Examines province-level distribution of real purchasing power parity (PPP) GDP per capita in Brazil, Russia, India, China, and South Africa (the “BRICS” economies).
  - Time series on province-level real GDP and population from national sources; IMF World Economic Outlook PPP exchange rate indicator used to convert to PPP-adjusted real GDP per capita (base year 2010).
  - Note: using national averages may overestimate incomes in rich provinces and underestimate incomes in poor provinces if substantial price variation exists across provinces.
- Key cross-country and time developments:
  - All BRICS economies enjoyed a period of strong income growth in the early 2000s driven by favorable external tailwinds and exits from crises.
  - The gap between average income per capita (in PPP-adjusted U.S. dollars) of BRICS economies and the United States narrowed significantly between 2002 and 2014.
  - Examples: in China and Russia, per capita income as a share of that in the United States increased by about 13 percentage points and 26 percentage points, respectively, between 2002 and 2014.
- Within-country disparities (selected highlights):
  - Richest provinces in some BRICS economies have incomes more than half of that in the United States (examples cited: Moscow, Russia; São Paulo, Brazil to a lesser extent).
  - Russia: incomes are close to seven times higher in the richest than in the poorest province.
  - India: incomes are 10 times higher in the richest than in the poorest province.
  - Brazil and China: the richest province is approximately four times better off than the poorest one.
  - South Africa: the richest province is two-and-a-half times better off than the poorest.
- Notes on terminology and choices:
  - “Province” refers to subnational administrative units immediately below the federal government; in Brazil and India these are referred to as states, and in Russia as federal districts.
  - São Paulo used for analysis though Distrito Federal is Brazil’s richest state, because Distrito Federal is a small jurisdiction with a large federal-government–related population share.
- Author: Felicia Belostecinic.

### Box 2.2 — Growing with Flows: Evidence from Industry-Level Data
- Purpose and identification:
  - Investigates causal impact of capital inflows on industry growth, focusing on channel where inflows relax credit constraints and reduce borrowing costs.
  - Uses panel fixed-effects approach exploiting cross-industry differences in external finance dependence.
  - Data: 28 manufacturing industries in 22 emerging market economies during 1998–2007. Total gross private capital inflows from the Institute of International Finance expressed in percent of GDP. Industry output growth computed as percent change in real output (industry output data reported in nominal U.S. dollars and deflated using the producer price index for finished goods).
  - External finance dependence measured following Rajan and Zingales (1998): ratio of capital expenditures net of cash flow from operations to total capital expenditures using U.S. data.
  - Empirical specification (reduced form): Gict = α + β1 Sic,t−1 + β2 CIct + β3 CIct * Di + θi + θc + θic + θt + εict, with standard errors clustered by industry-country.
- Main empirical findings:
  - Aggregate industry growth moves closely with capital inflows (Figure 2.2.1).
  - Industries more dependent on external finance grow disproportionately faster when located in countries with higher capital inflows; relationship is statistically significant after controlling for industry and country effects.
  - Results hold for annual growth rates and growth over three-year windows.
- Quantitative magnitude:
  - Using annual growth rates: relative to less dependent industries (25th percentile), industries at the 75th percentile of external finance dependence grow about 1.58 percent faster in a country at the 75th percentile of capital inflows than in a country at the 25th percentile of capital inflows. This equals approximately 14 percent of the observed sample mean of 11 percent.
  - Debt flows drive the relationship slightly more strongly:
    - An industry at the 75th percentile of external finance dependence grows 1.71 percent faster than one at the 25th percentile if domiciled in a country at the 75th percentile of debt capital inflows rather than one at the 25th percentile. This translates to 16 percent of the observed sample mean.
- Table 2.2.1 (Difference-in-Difference summary):
  - Economies with Low Capital Inflows (25th percentile) vs High Capital Inflows (75th percentile):
    - Highly Dependent Industries (75th percentile): 0.08 (low) vs 0.12 (high) — Difference 0.04
    - Less Dependent Industries (25th percentile): 0.06 (low) vs 0.09 (high) — Difference 0.03
    - Difference-in-Difference: 0.02 (low) vs 0.03 (high) — Difference 0.01
- Table 2.2.2 (Selected regression results; Annual Growth Rates, 1998–2007):
  - Columns shown for Total Inflows, Equity Inflows, Debt Inflows.
  - Coefficients (Annual Growth Rates, 1998–2007):
    - Share (t-1): –5.002***; –5.018***; –5.009*** (t-statistics in parentheses: (–5.33), (–5.40), (–5.33))
    - Capital Inflow: 0.004**; 0.003; 0.005** (t-statistics: (2.52), (1.03), (2.51))
    - Capital Inflow * Dependence: 0.008**; 0.004; 0.013*** (t-statistics: (2.34), (0.73), (2.93))
    - Constant: 0.856***; 0.853***; 0.867*** (t-statistics: (3.75), (3.76), (3.79))
    - Number of Observations: 4,396 across columns; R2: 0.257, 0.252, 0.259.
  - Growth over Three-Year Windows, 1999–2007 (selected coefficients):
    - Share (t-1): –0.951*; –0.956*; –0.971* (t-statistics: (–1.89), (–1.90), (–1.90))
    - Capital Inflow: 0.003; 0.005; 0.002 (t-statistics: (1.32), (1.42), (0.78))
    - Capital Inflow * Dependence: 0.006*; 0.004; 0.011* (t-statistics: (1.87), (0.47), (1.93))
    - Number of Observations: 1,570; R2: 0.548, 0.546, 0.547.
  - Fixed effects: Industry, Country, Industry*Country, Period. Number of economies: 22. Number of industries: 28.
  - Significance notation: ***, **, and * denote significance at the 1, 5, and 10 percent level, respectively.
- Robustness and notes:
  - Results robust to excluding China.
  - Results robust to using net inflows and capital inflows data from IMF’s International Financial Statistics.
  - Analysis focuses on pre-global financial crisis period (1998–2007) because the relationship differs markedly during the crisis and its aftermath.
- Author: Deniz Igan. Analysis based primarily on Igan, Kutan, and Mirzaei (2016).

### Box 2.3 — The Evolution of Emerging Market and Developing Economies’ Trade Integration with China’s Final Demand
- Purpose and data:
  - Explores evolution of emerging market and developing economies’ integration with China over two decades using data on countries’ value added in China’s final demand.
  - Uses Organisation for Economic Co-operation and Development–World Trade Organization Trade in Value Added database.
  - Trade in value added captures marginal contribution of a country’s domestic economy to production consumed in China, accounting for intermediates routed via other countries and discounting exports to China that are ultimately re-exported elsewhere.
- Aggregate integration trends:
  - China’s rapid growth led to a rapidly increasing share of global demand. All emerging market and developing economies have become more integrated with China over time (Figure 2.3.1).
  - Example metric: China consumed only 3 percent of the nondomestic global-value-added production of these countries in 1995; this increased to about 14 percent in 2011.
- Heterogeneity across country groups and drivers:
  - Commodity exporters and countries outside Asia experienced more substantial gains in integration with China in recent years, outpacing gains predicted by China’s growth alone (Figure 2.3.2).
  - Emerging market and developing economies in Asia have strong ties to China’s final demand; their rising exposure largely kept pace with China’s rising share of global GDP.
  - For countries outside Asia, China became an increasingly important source of demand by considerably more than suggested by China’s demand growth alone; a sharp rise in integration since 2000 is associated with China’s accession to the World Trade Organization in 2001.
- Sectoral composition:
  - For noncommodity exporters, sectoral composition of links with China has been relatively stable over time.
  - For commodity exporters, share of exports related to commodities rose dramatically during 2005–10, reflecting higher commodity prices and rapid infrastructure development in China.
  - From 1995 to 2011, commodity-exporting countries’ share of commodity-related exports to China increased by 20 percentage points, and by 12 percentage points to the rest of the world.
  - Commodity-related sectors defined here include: chemicals and nonmetal mineral products, basic metals and fabricated metal products, and mining and quarrying.
- Implications:
  - Greater integration with China’s final demand benefited many countries over the past two decades.
  - China’s recent slowdown poses challenges for trading partners as this source of demand growth slows; some elements of China’s economic transition (e.g., shifts in demand composition) could reshape impacts on partner countries’ exports and integration.
- Authors: Patrick Blagrave and Ava Yeabin Hong.

*Source: CHAPTER 2, World Economic Outlook: Gaining Momentum? — International Monetary Fund | April 2017*

### 1. Commodity versus Noncommodity Exporters

### 1. Commodity versus Noncommodity Exporters

### Sector composition and China’s rebalancing
- Figure 2.3.3 shows sector composition of value added in China’s final demand by sector: Manufacturing (excluding commodity related), Commodities and related, Services, Other.
- Figure 2.3.4 shows sector composition of commodity-exporting economies’ foreign value added by sector of final demand: Manufacturing (excluding commodity related), Commodities and related, Services, Other.
- China’s move up the value chain and the prospective boost to domestic consumption growth are likely to create opportunities for some economies, notably in emerging Asia.
- The increase in services trade associated with rebalancing and China’s increasing investment abroad are likely to continue to produce short-term benefits for some countries in the years ahead.

### Key quantitative notes on exporters
- Commodity exporter definition in Annex Table 2.1.2: commodity exports exceed 65 percent of total exports of goods, and net commodity exports account for at least 6 percent of GDP.

### Implications
- China’s transition entails short-term costs and long-term gains; see referenced discussion for detailed treatment of costs and gains.

### Sources for sector and trade data
- Organisation for Economic Co-operation and Development–World Trade Organization, Trade in Value Added database; and IMF staff calculations.

### Policy-relevant takeaway
- Economies tied to commodity-related demand face different sectoral exposure than noncommodity exporters; rebalancing in China shifts opportunities toward manufacturing up the value chain and services.

### Italicized source attribution
*International Monetary Fund | April 2017*

---

### Box 2.4 — Shifts in the Global Allocation of Capital: Implications for Emerging Market and Developing Economies

### Stylized facts on capital flows (uphill flows)
- Uphill flows (flows from poor to rich countries) intensified during most of the 2000s.
- Large and growing outflows from China and commodity-exporting emerging market and developing economies (especially fuel exporters) supported uphill flows.
- Capital outflows were dominated by official reserve accumulation used to back export-oriented growth models, smooth commodity windfalls, and self-insure against external shocks.

### Post-global financial crisis reversal
- After the global financial crisis, uphill flows slowed and have reversed more recently.
- Net outflows from emerging market and developing economies fell and reversed as China started to rebalance and the commodity income windfall vanished.
- The slowdown and reversal largely reflected movements in official foreign reserves, which started registering an overall decline a few years ago.
- Declines in foreign reserves imply private net capital inflows need not match total capital inflow behavior; some EMDEs have experienced increased total net inflows despite decreased private net inflows.

### Distributional and magnitude facts
- Across emerging market and developing economies, about 75 percent of countries were, on average, net recipients of inflows after 2000; excluding commodity exporters, this ratio increases to about 90 percent.
- Although these countries’ net capital inflows were small in relation to world GDP, their unweighted average inflow ratio to domestic GDP reached as high as almost 4 percent.
- Net foreign direct investment (FDI) inflows to emerging market and developing economies have stayed positive throughout the post-2000 period and have displayed far more stability than other capital account components.

### Interpretation and literature linkage
- Stability of FDI is consistent with findings that sovereign-to-sovereign flows, including foreign reserve accumulation, accounted for a large share of uphill flows; apart from such flows, data are consistent with private capital flowing from rich to poor countries.
- Nonreserve capital flows respond strongly to growth differentials.

### Correlation with growth
- Capital has tended to flow somewhat more to countries with higher per capita output growth, which is positively correlated with labor productivity growth.
- Data suggest a slightly positive relationship between overall net inflows and per capita output growth since 1990.
- The positive correlation between net inflows and per capita real GDP growth across around 150 emerging market and developing economies using 20-year rolling window averages is fairly stable through time.
- The analogous correlation has been positive for net FDI flows, although the relationship appears to have weakened over time.

### Forces determining future directions of flows
- Forces that could direct excess savings to EMDEs:
  - Stronger growth and infrastructure needs in EMDEs.
  - Structural changes such as population aging in advanced economies.
- Forces that could reverse flows:
  - Prospects of monetary policy normalization in advanced economies, especially if associated with a more expansionary U.S. fiscal stance or adverse balance sheet effects in EMDEs.
  - Rising global uncertainties, including the risk of protectionism.

### Overall short-term outlook
- A large and persistent downhill flow of capital seems unlikely to develop over the short term.

### Policy recommendations for EMDEs to reap benefits of inflows
- Further strengthen policy frameworks to address potential capital flow reversals triggered by higher U.S. interest rates and a stronger U.S. dollar.
- Exchange rate flexibility can help insulate economies from changes in global financial conditions, although additional tools may be needed at times to maintain orderly market conditions.
- Robust institutions and policy frameworks, including well-functioning domestic and international financial markets, remain crucial to harness the benefits of capital inflows.

### Figures and indicators referenced
- Figure 2.4.1: EMDEs: Current Account Balance by Group and Net Capital Inflows by Type (Percent of world GDP) — panels show Current Account Balance and Net Capital Inflows (Overall flows, FDI, Non FDI, Change in reserves).
- Figure 2.4.2: Distribution of EMDEs’ Average Current Account Balances, 2000–16 (Number of economies per interval).
- Figure 2.4.3: Correlation between Capital Flows and per Capita Real GDP Growth (Correlation coefficient, 20-year rolling windows).

### Italicized source attribution
*International Monetary Fund | April 2017*

---

### Annex 2.1 — Data, definitions, and sample

### Primary data sources used in chapter
- IMF World Economic Outlook (WEO) database
- Penn World Tables (version 9.0)
- World Bank World Development Indicators database
- Several other databases for external conditions variables and policy and other domestic attribute variables (see Annex Table 2.1.1 for indicator-by-source mapping).

### Key data definitions and constructions
- Real GDP per capita: Aggregate GDP and population data from Penn World Tables 9.0 to construct real GDP per capita at purchasing-power-parity adjusted U.S. dollars; aggregate GDP at constant national prices also from Penn World Tables 9.0.
- Country-specific external demand condition (equation 2.1):
  - For emerging market economy j in year t: external demand = ∑_{i∈Θ_j} ω_{i,t} * da_{i,t}, where ω_{i,t} is share of economy j’s exports accounted for by economy i (DOTS), da_{i,t} is annual growth rate of real domestic absorption in economy i (Penn World Tables 9.0), and Θ_j is set of trading partners accounting for at least 50 percent of total exports.
- Country-specific external financial conditions (equation 2.2):
  - For emerging market economy j in year t: external financial condition = (∑_{i∈Θ\j} K_inflow_{i,t}) / (∑_{i∈Θ\j} GDP_{i,t−1}), where K_inflow_{i,t} is gross inflows to economy i, GDP_{i,t−1} is GDP of economy i in U.S. dollars, Θ\j is related economies in same region excluding j.
- Commodity terms of trade (CTOT) indices (equations 2.3 and 2.4):
  - ∆ logCTOT_t = ∑_{j=1}^J ∆ log P_{j,t} τ_{i,j,t}, where P_{j,t} is relative price of commodity j (U.S. dollars divided by IMF unit value index for manufactured exports), and τ_{i,j,t} = (x_{i,j,t−1} − m_{i,j,t−1}) / GDP_{i,t−1}, with x and m being average export and import values of commodity j for economy i between t−1 and t−3 (United Nations Comtrade database).

### Annex Table 2.1.1 — Selected indicators and sources (indicator: source)
- Banking Crisis Indicator: Laeven and Valencia (2013)
- Bilateral Cross-Border Bank Claims: Bank for International Settlements
- Capital Account Openness: Quinn (1997); Aizenman, Chinn, and Ito (2010)
- Capital Inflows: IMF, Financial Flows Analytics database
- Capital Stock: Penn World Tables 9.0
- Commodity Terms of Trade: Gruss 2014
- Commodity Export Weights: United Nations Comtrade database; IMF, World Economic Outlook database
- Credit Boom Episodes: Dell’Ariccia and others (2016)
- Current Account Balance: IMF, World Economic Outlook database
- Deposit Money Banks' Assets Ratio to GDP (percent): World Bank, World Development Indicators database
- Employment: Penn World Tables 9.0
- Exchange Rate Stability Index: Aizenman, Chinn, and Ito (2010)
- Export Value of Goods (bilateral): IMF, Direction of Trade Statistics database
- External Debt Liabilities as a Share of GDP: Lane and Milesi-Ferretti (2007)
- Free Trade Agreements by Year of Signature of Agreement: DESTA, Free Trade Area database; October 2016 World Economic Outlook
- Free Trade Agreements Coverage: WTO Regional Trade Agreements database; October 2016 World Economic Outlook
- Human Capital: Penn World Tables 9.0
- Legal System and Property Rights Quality Index: Gwartney, Lawson, and Hall (2016)
- Nominal GDP: IMF, World Economic Outlook database
- Nominal Interest Rate: IMF, World Economic Outlook database
- Oil Price in U.S. Dollars: IMF, Global Assumptions database
- Polity Score (combined): Polity IV/Transparency International
- Population: Penn World Tables 9.0; United Nations Population database
- Public Debt as a Share of GDP: Mauro and others (2013); IMF, World Economic Outlook database
- Real GDP at Constant National Prices: IMF, World Economic Outlook database; Penn World Tables 9.0
- Real GDP in Purchasing Power Parity Terms: Penn World Tables 9.0
- Real Domestic Absorption: Penn World Tables 9.0
- Regulation Quality Index: Gwartney, Lawson, and Hall (2016)
- Sound Monetary Framework: Gwartney, Lawson, and Hall (2016)
- Tariffs: UNCTAD, Trade Analysis Information System; WTO Tariff Download Facility; IMF, Structural Reforms database; October 2016 World Economic Outlook

### Sample of emerging market and developing economies included (Annex Table 2.1.2)
- The sample includes all EMDEs currently classified as such by the WEO and those reclassified as “advanced” since 1996 (list provided in Annex Table 2.1.2).
- Note on commodity exporters: * denotes commodity exporters in the sample.

### Commodity price data
- Commodity price series start in 1960.
- Prices of 41 commodities are used, sorted into four broad categories.

### Italicized source attribution
*International Monetary Fund | April 2017*

### 1. Energy: coal, crude oil, and natural gas

### 1. Energy: coal, crude oil, and natural gas

### Commodity price data sources and indices
- Primary source: IMF’s International Financial Statistics database.
- Crude oil price: simple average of three spot prices—Dated Brent, West Texas Intermediate, and Dubai Fateh.
- World Bank’s Global Economic Monitor database used to extend price series of barley, iron ore, and natural gas from the IMF’s Primary Commodity Price System back to 1960.
- Coal price: Australian coal price, extended back to 1960 using the World Bank’s Global Economic Monitor database and U.S. coal price data from the U.S. Energy Information Administration.

### External conditions variables and correlations
- Annex Table 2.1.3 reports pairwise correlations between three external conditions variables:
  - Correlation between External Demand Conditions and External Financial Conditions: 0.1288
  - Correlation between External Demand Conditions and Commodity Terms of Trade: 0.0737
  - Correlation between External Financial Conditions and Commodity Terms of Trade: −0.00161
- Note: The low correlations suggest each dimension potentially exerts a separate influence.

### Rolling correlations (Annex Figure 2.1.1)
- Rolling correlation between country-specific external variables and global variables computed over nonoverlapping five-year windows for 1970–2014.
- World GDP growth defined as the weighted average (using market exchange rates) of growth in individual economies.
- CTOT = commodity terms of trade; EMDEs = emerging market and developing economies.

### Key note on variable definitions (from table footnote)
- One unit of external demand conditions corresponds to a 1 percentage point growth in domestic absorption of trading partners.
- One unit of external financial conditions corresponds to 1 percentage point of GDP in capital flows to regional economies.
- One unit of the commodity terms of trade corresponds to a 1 percent increase in the commodity terms of trade index (akin to a windfall income gain of 1 percent of GDP).

---

### Channels through which EMDEs narrowed income differentials with advanced economies (Annex 2.2)
- Production function used:
  - Y = A * K^α * (hL)^(1−α)  (equation (2.5) notation preserved)
- Output per worker expression:
  - y = Y / L = A^(1/(1−α)) * h * (K/Y)^(α/(1−α))  (equation (2.6) notation preserved)
- Decomposition comparing economy i to the United States:
  - (y_i / y_U.S.) = ( (A^(1/(1−α)))_i / ( (A^(1/(1−α)))_U.S. ) ) * (h_i / h_U.S.) * ( ((K/Y)^(α/(1−α)))_i / ((K/Y)^(α/(1−α)))_U.S. ).  (equation (2.7) notation preserved)
- Findings on the evolution of channels (Annex Figure 2.2.1):
  - During the 1970s, 1980s, and 1990s, movements in income-per-worker gaps mirrored movements in the TFP gap, with factor accumulation often moving in the opposite direction.
  - Over the past 15 years (relative to the publication), the relative output-per-worker gap has mirrored movements in the factor gaps more than TFP gaps.
  - Interpretation: TFP channel appears more important in the 1970s–1990s; factor accumulation has played a greater role in recent years.

### Figure notes (Annex Figure 2.2.1)
- Panels show changes in levels of selected variables relative to the United States in decades: 1970s, 80s, 90s, 2000s, 10s.
- Variables shown: GDP per Worker in PPP terms; Human Capital per Worker; Capital Intensity (defined as (K/Y)^(α/(1−α))); Total Factor Productivity.
- Boxplot conventions: horizontal line = median; upper/lower edges = top/bottom quartiles; red markers = top/bottom deciles.

---

### Estimation of the impact of external conditions on EMDE growth (Annex 2.3)

- Empirical framework:
  - General regression: g_it = α_i + μ_t + β X_it + γ Z_it + ε_it  (equation (2.8) notation preserved)
  - g_it: average annual growth rate of real GDP per capita in PPP terms in country i over period t (five-year nonoverlapping windows).
  - Z_it: three country-specific external conditions (external demand conditions, external financial conditions, commodity terms of trade).
  - X_it: parsimonious control set—initial level of income per capita, average rate of inflation, level of human capital, de jure measures of trade and financial openness (average import tariffs; index of restrictions to the capital account), and combined Polity IV index of governance characteristics.
- Estimation method:
  - Model estimated with generalized method of moments (GMM) for dynamic panel models (Arellano and Bond (1991); Arellano and Bover (1995)).
  - Difference GMM estimator used to address dynamic panel bias and potential endogeneity.

### Main estimation results (Annex Table 2.3.1)
- Dependent variable: GDP per Capita Growth Rate (average annual, five-year windows, sample period 1970–2014).
- Columns (1)–(4) estimated by GMM; columns (5)–(8) by OLS with country fixed effects.
- Selected coefficient estimates (coefficient (standard error)):
  - External Demand Conditions:
    - Col (1): 0.524 (0.203) **
    - Col (2): 0.421 (0.192) **
    - Col (3): 0.331 (0.199)
    - Col (4): 0.243 (0.189)
  - External Financial Conditions:
    - Col (1): 0.266 (0.099) ***
    - Col (2): 0.186 (0.085) **
    - Col (3): 0.339 (0.096) ***
    - Col (4): 0.289 (0.086) ***
  - Commodity Terms of Trade:
    - Col (1): 0.453 (0.238) *
    - Col (2): 0.481 (0.249) *
    - Col (3): 0.539 (0.220) **
    - Col (4): 0.538 (0.218) **
- Estimation details:
  - Number of Observations by column: 505, 517, 509, 497, 587, 601, 592, 578.
  - Number of Economies by column: 81, 84, 83, 80, 82, 84, 83, 81.
  - R^2 (reported for some specifications): 0.411, 0.422, 0.417, 0.432.
- Specification test p-values:
  - Second-Order Correlation Test: 0.863, 0.913, 0.567, 0.507 (across columns reported).
  - Hansen Test: 0.149, 0.173, 0.197, 0.201 (across columns reported).
- Statistical significance notation preserved: ***, **, * denote significance at the 1, 5, and 10 percent level, respectively.
- Note reiteration: One unit of each external variable corresponds to the units defined above (1 percentage point growth in domestic absorption of trading partners; 1 percentage point of GDP in capital flows to regional economies; 1 percent increase in CTOT).

### Robustness exercises (Annex Table 2.3.2) — all exercises estimated with difference GMM and include all three external conditions jointly
- Summary of robustness experiment designs:
  - Column (1): excludes China from estimation sample.
  - Column (2): excludes all large emerging market and developing economies (members of the Group of Twenty in the sample).
  - Column (3): excludes the smallest economies (collectively accounted for less than 5 percent of EMDE aggregate GDP in PPP terms in 2011).
  - Columns (4)–(6): additional checks addressing potential endogeneity of external financial conditions and CTOT; column (4) instruments external financial conditions with its own lags; column (5) uses a country-specific financial-flows-weighted average of interest rates in France, Germany, Japan, United Kingdom, United States as an additional instrument; column (6) uses an alternative CTOT index that weights individual commodity price fluctuations by overall commodity trade rather than GDP.
- Selected coefficient estimates from Annex Table 2.3.2 (coefficient (standard error)):
  - External Demand Conditions:
    - Col (1): 0.401 (0.194) **
    - Col (2): 0.361 (0.204) *
    - Col (3): 0.153 (0.322)
    - Col (4): 0.408 (0.191) **
    - Col (5): 0.400 (0.196) **
    - Col (6): 0.372 (0.214) *
  - External Financial Conditions:
    - Col (1): 0.204 (0.087) **
    - Col (2): 0.223 (0.101) **
    - Col (3): 0.194 (0.089) **
    - Col (4): 0.199 (0.086) **
    - Col (5): 0.244 (0.093) ***
    - Col (6): 0.330 (0.111) ***
  - Commodity Terms of Trade:
    - Col (1): 0.502 (0.255) **
    - Col (2): 0.454 (0.245) *
    - Col (3): 1.036 (0.293) ***
    - Col (4): 0.195 (0.053) ***
    - Col (5): 0.473 (0.246) *
    - Col (6): 0.954 (0.213) ***
- Specification test p-values (examples across robustness columns):
  - Second-Order Correlation Test: 0.512, 0.462, 0.681, 0.602, 0.693, 0.523.
  - Hansen Test: 0.198, 0.235, 1.000, 0.138, 0.327, 0.207.
- Interpretations from robustness checks:
  - Excluding large EMDEs (including China) does not qualitatively change the finding that external conditions significantly affect medium-term growth.
  - Instrumenting external financial conditions yields coefficient estimates that are marginally larger and more statistically significant than baseline.
  - Using an alternative CTOT index (trade-weighted) yields a larger coefficient due to larger variability in the alternative index; qualitative results unchanged.
  - Interquartile range comparison: alternative CTOT index average annual change interquartile range = −2.8 to 3 percent; baseline CTOT index interquartile range = −0.4 to 0.3 percent.

### Endogeneity and sample composition notes
- Baseline estimation attempts to mitigate endogeneity concerns by including all three external conditions jointly and time fixed effects.
- Robustness exercises (excluding large EMDEs; instrumenting variables; alternative CTOT) address potential reverse causality or omitted variable bias.
- Baseline sample includes many very small economies; column (3) robustness excludes smallest economies (collective share < 5 percent of EMDE aggregate GDP in PPP terms in 2011).

---

### Identification of growth acceleration episodes (Annex 2.4)
- Trend growth rate definition:
  - g_{t,t+h} is least squares growth rate of real GDP per capita at constant national prices (y) from t to t + h estimated over rolling windows of six years [t, t + h], using equation: ln(y_{t+i}) = α + g_{t,t+h} × i, i = 0, ..., h. (equation (2.9) notation preserved)
- Episode definition (horizon h set at five years in the baseline case):
  - The trend growth rate of real GDP per capita is at least 3.5 percent a year (g_{t,t+h} ≥ 3.5).
  - The trend growth rate during the episode exceeds the trend growth rate during the preceding equal-length period.
- Data notes:
  - Episodes identified up to the year 2010 using real income per capita from PWT 9.0 through 2014 and extended to 2015 using the growth rate of real income per capita from the WEO database.
- Reference methodology: follows Hausmann, Pritchett, and Rodrik (2005).

*Source: IMF staff calculations; extracted from “1. Energy: coal, crude oil, and natural gas” and Annexes 2.1–2.4 in the provided text.*

### CHAPTER 2 ROaDs LEss TRavELED: GROWTh IN EMERGING MaRKET aND DEvELOpING ECONOMIEs IN a COMpLICaTED ExTERNaL ENvIRONMENT

### CHAPTER 2 ROaDs LEss TRavELED: GROWTh IN EMERGING MaRKET aND DEvELOpING ECONOMIEs IN a COMpLICaTED ExTERNaL ENvIRONMENT

### Definitions and Identification of Episodes
- Persistent acceleration episode identification criteria:
  - Trend growth increase of at least 2 percentage points: (g_{t,t+h} − g_{t,t−h} ≥ 2).
  - Level condition: real GDP per capita at end of episode at least as large as the maximum level recorded prior to onset: (y_{t,t+h} ≥ max{y_i}, ∀ i ≤ t).
  - Persistence requirement: no subsequent reversal or banking crisis within three years before or after end of the acceleration episode.
- Reversal episode identification criteria:
  - Trend growth decline of at least 2 percentage points: (g_{t,t−h} − g_{t,t+h} ≥ 2).
  - Real GDP per capita declines: average level during [t,t+h] is lower than average during [t−h,t]: (ȳ_{t,t+h} ≤ ȳ_{t−h,t}).
- Episodes identified:
  - 95 episodes of persistent accelerations (Annex Table 2.4.1).
  - 125 episodes of reversals (Annex Table 2.4.2).

### Data and Methodology for External Conditions Analysis
- Two dummy variables constructed:
  - Dummy = 1 for economy-years identified as persistent acceleration episodes (and first lead t+1 and lag t−1 around each episode), zero otherwise.
  - Dummy = 1 for economy-years identified as reversal episodes (and first lead and lag), zero otherwise.
- Probability model:
  - Pr(episode_{it} = 1) = Φ(γZ_{it}) where Z_{it} are moving averages (between t+1 and t+h) of three country-specific external conditions variables, and Φ is a nonlinear function (probit or logit).
- Baseline (logit) specification (equation 2.11):
  - log(Pr(episode_{it}=1) / (1 − Pr(episode_{it}=1))) = γZ_{it} + β X_{it} + α_i + ε_{it}
  - X_{it} are controls (moving averages between t−3 and t−1) including de jure integration, credibility of policy frameworks, and other domestic covariates; α_i captures country fixed effects.
- Robustness: linear probability model tested; significance robust.

### Logit Estimates — Main Coefficient Findings (Annex Tables 2.5.1 and 2.5.2)
- Persistent Accelerations (Annex Table 2.5.1): reported coefficients (changes in odds ratio) and robust standard errors in parentheses
  - External Demand:
    - No Country or Time Fixed Effects: 1.248*** (0.087)
    - Country Fixed Effects and Other Controls: 1.607*** (0.151)
    - Time Fixed Effects Only: 1.095 (0.097)
    - Country and Time Fixed Effects: 1.158** (0.085)
    - Random Effects: 1.330*** (0.119)
    - Probit Random Effects: 1.165*** (0.052)
    - Baseline Country Fixed Effects: 1.384*** (0.088)
  - External Financial:
    - No Country or Time Fixed Effects: 1.209*** (0.045)
    - Country Fixed Effects and Other Controls: 1.227*** (0.050)
    - Time Fixed Effects Only: 1.103** (0.050)
    - Country and Time Fixed Effects: 1.098** (0.044)
    - Random Effects: 1.243*** (0.049)
    - Probit Random Effects: 1.123*** (0.021)
    - Baseline Country Fixed Effects: 1.240*** (0.034)
  - Change in Terms of Trade:
    - No Country or Time Fixed Effects: 0.970 (0.047)
    - Country Fixed Effects and Other Controls: 1.042 (0.091)
    - Time Fixed Effects Only: 0.935 (0.046)
    - Country and Time Fixed Effects: 1.040 (0.076)
    - Random Effects: 1.007 (0.063)
    - Probit Random Effects: 1.009 (0.030)
    - Baseline Country Fixed Effects: 1.052 (0.066)
  - Model fit / sample notes:
    - Number of Economies varies (e.g., 110 in several columns; 116 in Probit Random Effects).
    - Number of Observations examples: 4,176; 1,325; 2,279; 4,322; 2,279 (varies by specification).
- Reversals (Annex Table 2.5.2): reported coefficients (changes in odds ratio) and robust standard errors in parentheses
  - External Demand:
    - No Country or Time Fixed Effects: 0.818*** (0.047)
    - Country Fixed Effects and Other Controls: 0.738*** (0.067)
    - Time Fixed Effects Only: 0.841*** (0.046)
    - Country and Time Fixed Effects: 0.793*** (0.061)
    - Random Effects: 0.736*** (0.055)
    - Probit Random Effects: 0.851*** (0.033)
    - Baseline Country Fixed Effects: 0.655*** (0.038)
  - External Financial:
    - No Country or Time Fixed Effects: 0.822*** (0.037)
    - Country Fixed Effects and Other Controls: 0.710*** (0.043)
    - Time Fixed Effects Only: 1.014 (0.061)
    - Country and Time Fixed Effects: 0.977 (0.055)
    - Random Effects: 0.788*** (0.041)
    - Probit Random Effects: 0.876*** (0.023)
    - Baseline Country Fixed Effects: 0.774*** (0.028)
  - Change in Terms of Trade:
    - No Country or Time Fixed Effects: 0.933* (0.039)
    - Country Fixed Effects and Other Controls: 0.851* (0.074)
    - Time Fixed Effects Only: 0.976 (0.041)
    - Country and Time Fixed Effects: 0.973 (0.028)
    - Random Effects: 0.935** (0.031)
    - Probit Random Effects: 0.963** (0.017)
    - Baseline Country Fixed Effects: 0.941** (0.027)
  - Model fit / sample notes:
    - Number of Economies and Observations vary (examples: Observations 4,176; 1,184; 2,835; 4,135; 4,322; 2,835).
- Interpretation summary directly from estimates:
  - External demand and external financial conditions are robustly positively associated with the odds ratio of persistent accelerations across specifications.
  - For reversals, external demand is robustly associated with lower odds of reversal; external financial conditions lose statistical significance when time fixed effects are included in the regression (columns (3) and (4) of Annex Table 2.5.2), likely reflecting common time-varying drivers of capital flows.
  - The commodity terms-of-trade variable is not significant in full-sample specifications for persistent accelerations, and its significance for reversals depends on inclusion of time fixed effects (time fixed effects likely capture common drivers of commodity prices).

### Marginal Effects and Robustness Tests
- Average marginal effects computed from logit estimates (equation 2.12); baseline results evaluate external conditions at sample means.
- Robustness to sample splits:
  - Results robust when excluding China or excluding G20 economies (Annex Figure 2.5.2).
- Robustness to episode duration:
  - Reestimating episodes with h = 7 instead of h = 5; marginal effects remain statistically significant with similar pattern (Annex Figure 2.5.3).
- Summary from Annex Figure 2.5.1 and related figures:
  - Change in the odds ratio (percent) and marginal effects (percentage points) presented for different estimation procedures; confidence intervals reported (vertical lines denote 90 percent confidence intervals).

### Channels: Capital-Led versus Non-Capital-Led Accelerations
- Classification:
  - Capital-led accelerations: contribution to growth from capital deepening during the episode exceeds the country’s average contribution to growth from capital deepening for the entire sample (capital measured using capital-output ratio rather than capital per worker).
  - Non-capital-led accelerations: remaining persistent acceleration episodes.
- Counts:
  - 61 capital-led acceleration episodes.
  - 34 non-capital-led acceleration episodes.
- Differential effects of external conditions (Annex Figure 2.5.4 summary):
  - Favorable external demand raises the probability of non-capital-led acceleration episodes relatively more than capital-led episodes.
  - Favorable external financing raises the probability of capital-led episodes more than non-capital-led episodes.

*Source: IMF staff calculations, CHAPTER 2 ROaDs LEss TRavELED: GROWTh IN EMERGING MaRKET aND DEvELOpING ECONOMIEs IN a COMpLICaTED ExTERNaL ENvIRONMENT, April 2017.*

### Annex 2.6. Analysis of Domestic Attributes in

### Annex 2.6. Analysis of Domestic Attributes in Mediating the Impact of External Conditions

### Data and Measurement of Domestic Attributes
- Free trade agreements: flows by year of signature from the October 2016 World Economic Outlook (Chapter 2) using the Design of Trade Agreements database; complemented with stock of free trade agreements in effect from the World Trade Organization Regional Trade Agreements database.
- Financial depth: proxied by total assets held by deposit money banks as a share of GDP from the World Bank’s Global Financial Development database.
- Sound credit growth: identification of excessive credit growth (credit booms) follows Dell’Ariccia and others (2016).
- Capital account openness: index is an update of the Quinn (1997) measure based on the narrative portion of the IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions; higher value denotes fewer restrictions.
- Current account balance: current account balance as a share of GDP from the IMF World Economic Outlook database.
- Exchange rate flexibility: degree based on the de facto index developed by Aizenman, Chinn, and Ito (2010).
- Public debt: ratio of public debt to GDP from Mauro and others (2013).
- Sound monetary framework: proxied by the sound money index from Gwartney, Lawson, and Hall (2016); standardized measure combining indicators on growth of money supply, level and volatility of inflation, and the possibility of owning foreign currency bank accounts.
- Regulation, legal system, and property rights: indices from Gwartney, Lawson, and Hall (2016), compiling indicators from Global Competitiveness Report, International Country Risk Guide, Doing Business, World Developments Indicators, and International Financial Statistics.

### Empirical Specification and Methodology
- Direct-effect specification: variation of the logit regression (2.11) with Xit including the moving average (between t–3 and t–1) of one domestic policy or attribute at a time; controls include external conditions and country fixed effects.
- Interaction specification: logit with interaction terms (equation (2.13)):
  - log(Pr(episodeit = 1)/(1 − Pr(episodeit = 1))) = γ zit + β xit + δ (zit × xit) + αi + εit
  - zit is one of three country-specific external conditions; xit is the moving average between t–3 and t–1 of the domestic attribute; αi captures time-invariant country fixed effects.
- Marginal effects:
  - Main exercise (Figure 2.19): compares marginal effects when the domestic attribute is at the 25th percentile versus the 75th percentile, with the external conditions variable set at its sample median.
  - Annex Figure 2.6.2: computes changes in the marginal effect of external financial conditions when the external financial conditions variable is set at the 25th (less favorable) and 75th (more favorable) percentiles, and the domestic attribute varies from the 25th to the 75th percentile.
- Use of marginal effects is emphasized because interaction coefficients in nonlinear logit models are not sufficient to infer how the effect of one independent variable depends on another (Ai and Norton 2003).

### Direct Effects: Key Regression Results (Logistic Estimates)
- Persistent accelerations (Annex Table 2.6.1): notable coefficients (changes in odds ratio)
  - External Demand: examples of reported odds ratios include 1.266***, 1.296***, 1.234***, 1.382***, 1.275***, 1.285***, 1.264***, 1.268***, 1.282***, 1.352***, 1.279***, 1.293***, 1.401*** (robust standard errors reported in parentheses).
  - External Financial: series includes 1.200***, 1.217***, 1.209***, 1.193***, 1.223***, 1.213***, 1.224***, 1.195***, 1.204***, 1.218***, 1.213***, 1.215***, 1.215***.
  - Deposit Money Banks’ Assets to GDP: 1.007** and 1.009** (standard errors (0.003) and (0.004)).
  - Sound Monetary Framework: 1.120** (standard error (0.063)).
  - Legal System and Property Rights: 1.189** (standard error (0.102)).
  - Model Chi-Squared Test statistics reported (examples): 44.99***, 51.42***, 49.63***, 40.97***, 56.28***, 56.67***, 54.39***, 48.60***, 48.73***, 47.14***, 37.43***, 47.29***, 45.49***.
  - Number of Economies (examples): 113, 116, 114, 92, 115, 116, 116, 114, 115, 103, 103, 105, 81.
  - Number of Observations (examples): 3,044; 3,793; 3,203; 3,292; 4,159; 4,048; 3,880; 4,138; 3,643; 3,353; 2,871; 2,780; 1,699.
- Reversals (Annex Table 2.6.2): notable coefficients (changes in odds ratio)
  - External Demand: examples include 0.820**, 0.694***, 0.686***, 0.705***, 0.806***, 0.731***, 0.717***, 0.694***, 0.755***, 0.700***, 0.702***, 0.749***, 0.607*** (standard errors in parentheses).
  - External Financial: 0.783***, 0.774***, 0.740***, 0.786***, 0.804***, 0.804***, 0.779***, 0.809***, 0.784***, 0.790***, 0.715***, 0.691***, 0.701***.
  - Deposit Money Banks' Assets to GDP: 0.988* and 0.987 (standard errors (0.007) and (0.011)).
  - External Debt to GDP: 0.999 and 1.005*** (standard errors (0.001) and (0.002)).
  - Exchange Rate Stability Index: 2.783*** and 2.410 (standard errors (0.865) and (1.834)).
  - Sound Monetary Framework: 0.925* (standard error (0.039)).
  - Model Chi-Squared Test statistics reported (examples): 42.95***, 45.73***, 55.70***, 50.31***, 39.71***, 45.60***, 50.82***, 61.38***, 42.21***, 40.44***, 43.97***, 50.45***, 72.65***.
  - Number of Economies and Observations match those reported in Annex Table 2.6.1 for corresponding specifications.

### Main Empirical Findings (Economic Interpretation)
- Persistent accelerations:
  - More financial depth (higher deposit money banks’ assets to GDP), a sound monetary framework, and better quality of institutions significantly increase the odds ratio of experiencing a persistent acceleration (Annex Table 2.6.1).
- Reversals:
  - A sound monetary framework and more financial depth significantly reduce the odds ratio of experiencing a reversal (Annex Table 2.6.2).
  - Lower exchange rate flexibility (i.e., greater exchange rate stability measured by the exchange rate stability index) increases the odds ratio of experiencing a reversal (Annex Table 2.6.2).
- The coefficients on domestic attribute variables are interpreted as impacts, in percent, on the odds ratio of experiencing a growth episode versus not experiencing one: values below (above) 1 indicate lower (higher) odds of experiencing an episode versus not experiencing an episode for higher values of the domestic attribute variable.

### Marginal Effects and Economic Relevance
- Annex Figure 2.6.1: shows the marginal effect (change in the likelihood of a growth episode, in percentage points) when a domestic attribute moves from the 25th percentile to the 75th percentile of its sample distribution.
  - The exchange rate regime is interpreted such that the 25th percentile corresponds to a fully flexible exchange rate regime and the 75th percentile corresponds to a fixed exchange rate regime.
- Annex Figure 2.6.2: shows how the marginal effect of external financial conditions on the likelihood of reversal episodes changes when selected domestic attributes improve, evaluated at less favorable (25th percentile) and more favorable (75th percentile) external financial conditions.
  - The figure notes that a negative value implies a further reduction in the probability of a reversal.
- Confidence intervals:
  - Figures report vertical lines denoting 90 percent confidence intervals.
- Illustrative magnitudes (figure axis labels and ranges preserved as in source):
  - Marginal effects plotted across domestic attributes show ranges between −8 and 10 percentage points in the visualized charts for 1. Persistent Accelerations and 2. Reversals (Annex Figure 2.6.1) and between −4 and 1 percentage point range for specific attributes in Annex Figure 2.6.2 (Bank assets, Sound credit growth, Exchange rate flexibility).

### Interpretation and Robustness Notes
- Some indices (regulation, legal system, property rights) compile multiple indicators from several sources; while individual indicators may be vulnerable to perception-based rankings and measurement uncertainties, the constructed indices combine several indicators and may be less sensitive to outliers and subjectivity.
- The test of the difference in marginal effects assumes a t-distribution.
- Estimations in Annex Tables 2.6.1 and 2.6.2 do not include country fixed effects (note in tables).

*Source: IMF staff calculations (Annex 2.6, World Economic Outlook: Gaining Momentum?, April 2017).*

### CHAPTER 2

### CHAPTER 2  ROaDs LEss TRavELED: GROWTh IN EMERGING MaRKET aND DEvELOpING ECONOMIEs IN a COMpLICaTED ExTERNaL ENvIRONMENT

### Overview
- This chapter documents a downward trend in the labor share of income since the early 1990s, with heterogeneous evolution across countries, industries, and workers of different skill groups, using newly assembled data for a large sample of advanced and emerging market and developing economies.
- Authors: Mai Chi Dao, Mitali Das (team leader), Zsoka Koczan, Weicheng Lian, with contributions from Jihad Dagher and support from Benjamin Hilgenstock and Hao Jiang. Robert Feenstra and Brent Neiman were external consultants.

### Key findings
- The labor share of income has been on a downward trend in many countries.
- In advanced economies:
  - Labor income shares began trending down in the 1980s.
  - They reached their lowest level of the past half century just prior to the global financial crisis of 2008–09, and have not recovered materially since.
- In emerging market and developing economies:
  - Data are more limited, but in more than half of them—especially the larger economies in this group—labor shares have declined since the early 1990s.
- The decline in the labor share has been diverse across countries within both advanced and emerging market groups.
- The decline in labor share has been concomitant with increases in income inequality:
  - Lower-skilled workers have borne the brunt of the fall in labor share, with persistent declines in middle-skill occupations and income losses for middle-skilled workers in advanced economies.
  - Capital ownership is typically concentrated among the top of the income distribution and hence an increase in the share of income accruing to capital tends to raise income inequality.

### Analytical framework and exact identity
- The labor share of income is defined and decomposed as:
  - (wL)/(PY) = (w/P) / (Y/L)
    - where w is the money wage (including benefits) per worker,
    - L is employment (hours worked),
    - Y is real output,
    - Y/L is labor productivity,
    - P is the GDP deflator.
  - w/P is the wage expressed in units of domestic output (the real or product wage).
- A falling labor share implies that product wages grow more slowly than average labor productivity.
- The product wage may differ from the consumption wage because the latter takes into account the terms of trade (the price of imports in terms of exports).

### Main drivers identified
- Two leading global explanations emphasized (especially for the United States and advanced economies):
  - Technological progress.
  - Globalization of trade and capital.
- Specific quantitative assessment (as described):
  - In advanced economies, technological progress—reflected in the steep decline in the relative price of investment goods—along with varying exposure to routine-based occupations, explains about half the overall decline in the labor share, with a larger negative impact on the earnings of middle-skilled workers.
  - In emerging markets, labor share evolution is explained predominantly by the forces of global integration, particularly the expansion of global value chains that contributed to raising the overall capital intensity in production.

### Implications and broader consequences
- Low productivity growth, if persistent, limits expectations of future wage growth absent a reversal in favor of higher labor shares.
- Rising inequality associated with falling labor shares can fuel social tension and may harm economic growth.
- As the global economy struggles with subpar growth, unequal sharing of gains has strengthened backlash against economic integration and bolstered support for inward-looking policies.
- The chapter emphasizes that many advanced and emerging market economies experienced declines through somewhat synchronized evolutions—through domestic business cycles and structural transformation—suggesting key driving forces that are likely global, while varying exposures to common global trends help explain cross-country diversity.

### Evidence and empirical notes
- Figures referenced and datasets used include:
  - Figure 3.1 showing evolution of labor share for advanced economies and emerging market and developing economies, with year fixed effects normalized to reflect the level of the labor share in 2000.
  - Figure 3.2 documenting the association between labor shares and Gini coefficients (levels and within-country changes), noting statistical significance markers (*** indicates 1 percent statistical significance; ** indicates 5 percent statistical significance).
- The chapter cites related literature assessing the roles of technology, trade, and capital flows in labor share dynamics.

*Source: CHAPTER 2, text - CHAPTER 2, https://www.imf.org/-/media/files/publications/weo/2017/april/pdf/text.pdf*

### CHAPTER 3

### CHAPTER 3
 UNDERsTaNDING ThE DOWNWaRD TREND IN LabOR INCOME shaREs

### Overview and purpose
- Examines why labor shares of income have declined since the early 1990s and how trends differ across countries, industries, and skill groups.
- Two key contributions:
  - Tests whether rapid advances in information and communications technology and the steep decline in the relative price of investment goods have lowered labor shares by encouraging automation of routine tasks.
  - Highlights that the relative price of investment declined steeply in advanced economies but experienced a milder decline or even rose in some emerging market economies (Annex Figure 3.4.2).
- Measures of global integration used in the chapter:
  - Trade in final goods and services: proxied by value-added exports and imports relative to GDP.
  - Participation in global value chains: proxied by the sum of forward and backward linkages.
  - Financial integration: proxied by the sum of external assets and liabilities excluding reserves, in percent of GDP.
- Recognizes conceptual and empirical difficulty in separating effects of technology and global integration; results interpreted in light of these challenges.

### Major questions addressed
- How widespread has the decline in the labor share of income been since the early 1990s? How do trends differ across countries, industries, and skill groups?
- What are the key drivers of the labor share of income and through which mechanisms do they operate? Do drivers vary between advanced economies and emerging market and developing economies, industries, and skill groups?
- How have exposures to routinization and participation in global value chains affected labor shares? What roles have regulations of labor and product markets played?

### Summary of main findings
- Between 1991 and 2014, the labor share declined in 29 of the largest 50 economies; those 29 economies accounted for about two-thirds of world GDP in 2014.
- Across industries, labor income shares have declined in 7 of the 10 major industries, with the sharpest declines in more tradable sectors such as manufacturing, and transportation and communication.
- Shift-share decomposition (1993–2014):
  - More than 90 percent of changes in labor income shares reflect within-industry changes rather than sectoral reallocation.
  - Important exception: China, where reallocation from agriculture to other industries accounts for the majority of the decline in the labor share of income.
- Technology and routinization in advanced economies:
  - Technological advancement, measured by long-term change in the relative price of investment goods, together with initial exposure to routinization, have been the largest contributors to the decline in labor income shares in advanced economies.
  - Empirical analysis suggests that about half of the total decline in labor shares can be traced to the impact of technology.
  - For a given change in the relative price of investment, economies with high exposure to routinization experienced about four times the decline in labor income shares than those with low exposure.
- Global integration:
  - Has played a role largely by lowering labor shares in tradables sectors.
  - In emerging market economies as a whole, participation in global value chains appears to be an important factor behind the decline in the labor share of income.
  - Financial integration in emerging market economies has partly offset declines by raising labor shares, conceivably by lowering the cost of capital and reflecting limited substitutability between labor and capital.
- Heterogeneity:
  - For emerging market economies in the aggregate, there is no discernible role of technology in the evolution of labor shares, reflecting both a relatively mild decline in the relative price of investment goods and much lower exposure to routinization.
  - Results for the emerging market composite mask significant differences across individual economies reflecting diversity in evolution of relative prices of investment goods and initial routinization exposures.
- Skill composition effects:
  - Decline in labor shares driven by technology and global integration has been particularly sharp for middle-skilled labor.
  - During 1995–2009, combined labor income share of low- and middle-skilled labor was reduced by more than 7 percentage points, while the global high-skilled labor share increased by more than 5 percentage points.
- Robustness to measurement adjustments:
  - Adjustments for self-employment and capital depreciation rates can have important effects on both the level and evolution of labor shares (Box 3.4).
  - Findings about key drivers of the unadjusted labor shares are robust to adjustments for both self-employment and depreciation rates.

### Drivers and mechanisms (conceptual summary)
- Technology channel:
  - Decline in the relative price of investment goods lowers firms’ user cost of capital, giving incentives to substitute capital for labor (Karabarbounis and Neiman 2014).
  - Impact depends on elasticity of substitution between labor and capital (see Box 3.2).
  - Automation of routine tasks driven by information and communications technology contributes to displacement of routine occupations.
- Global integration channel:
  - Trade and financial integration increased sharply over past 25 years via removal of restrictions, lower transport/communication costs, and technology diffusion.
  - Integration induced domestic factor reallocation in response to import competition and relocation of lower-skill, labor-intensive production stages to cheaper locations, potentially lowering labor bargaining power.
  - Classical trade theory predicts differing effects by factor endowments, but the chapter notes integration involves cross-border factor movement, technology transfers, and bargaining-power shifts, explaining why both advanced and emerging economies can see lower labor shares.
- Other channels:
  - Regulation of labor and product markets affects profit size and distribution between capital and labor.
  - Increased industry concentration and agglomeration may have raised profit shares and lowered labor shares.
  - Policy changes (e.g., declining corporate income tax rates) may have strengthened incentives to substitute capital for labor.
  - Institutional changes (e.g., declining unionization) may have lowered labor bargaining power.

### Empirical approaches and data
- Two complementary empirical approaches:
  - Shift-share analysis to distinguish within-industry declines from between-industry composition effects.
  - Core empirical analysis quantifying how drivers track long-term changes in labor income shares using a newly assembled dataset of aggregate and sectoral labor shares for advanced and emerging market and developing economies, and labor shares by skill groups.
- New data:
  - Sectoral labor share data on emerging market and developing economies compiled from official sources (described in Annex 3.3 and Dao and others (forthcoming)).
- Global trends considered:
  - Focus period: 1991 through 2014, during which the global labor share declined by some 2 percentage points.
  - Global labor share declined 5 percentage points to its trough in 2006 and trended up about 1.3 percentage points thereafter.

### Stylized facts and heterogeneity
- Global and country-group patterns:
  - Decline in global labor share since 1980s; focus on 1991–2014 due to major structural changes (China, India, former Eastern bloc entries).
  - Labor share declined in 4 of the world’s 5 largest economies, led by the steepest decline in China; labor share in the United Kingdom trended up.
  - In a sample of 35 advanced economies (1991–2014), labor share declined in 19 economies, which accounted for 78 percent of 2014 advanced economy GDP.
  - Standard deviation of long-term changes in labor shares: 4.8 across emerging market and developing economies and 1.5 across advanced economies.
  - In a sample of 54 emerging market and developing economies, the labor share declined in 32 economies, which accounted for about 70 percent of 2014 emerging market GDP.
- Industry patterns:
  - Global level: sharpest decline in manufacturing, followed by transportation; some sectors (food and accommodation, agriculture) saw an increase.
  - Advanced economies: declines concentrated in tradable sectors.
  - Emerging market and developing economies: sharpest decline observed in agriculture; labor shares rose in manufacturing and especially in health services and construction—partly reflecting China’s industrial evolution since 1993.

*International Monetary Fund | April 2017*

### CHAPTER 3

### CHAPTER 3

### Observed Trends in Labor Income Shares and Skill Composition
- The decline in middle-skilled labor’s income share was driven primarily by a drop in their relative wage rate.
- The share of middle-skill employment in the total workforce remained stable or even rose.
- The labor share decline for low-skilled labor and the increase for high-skilled labor were driven, to a large extent, by the diverging trend in employment composition, reflecting rising levels of education.
- The patterns hold for both advanced and emerging market and developing economies, but they are more pronounced in advanced economies, consistent with evidence of wage and employment polarization.
- The decline in the labor share of income for low- and middle-skill workers has been especially pronounced, with the decline for middle-skill workers driven primarily by a decline in their relative wage rate.
- While the downward trend in the labor share of income is fairly broad based across countries and industries, there is tremendous diversity in its evolution.

### Key Concept: Elasticity of Substitution Between Capital and Labor
- The elasticity of substitution between capital and labor measures how easily one is substituted with the other when their relative cost changes.
- If the elasticity of substitution is larger than 1 (capital is highly substitutable for labor), a decline in the relative cost of capital drives firms to substitute capital for labor so much that the labor share of income declines.
- If, for tasks offshored from high-wage to low-wage countries, capital cannot easily be replaced by labor (the elasticity of substitution is lower than 1), the labor income share may decline in the receiving country.
- The constant elasticity of substitution production function originates in Arrow and others (1961) and has been used to analyze the functional distribution of income.

### Technological Advancement: Mechanisms and Evidence
- Technological progress, embodied in faster productivity growth in the capital goods sector relative to the rest of the economy, lowers the price of investment goods and thus induces firms to substitute capital for labor.
- Rapid advance of information and communications technology accelerates automation of routine tasks and thus induces firms to disproportionately substitute capital for labor where exposure to such tasks is larger.
- Interaction: a decline in the relative price of investment goods triggers greater substitution away from labor, with larger impacts where labor performs more routine tasks.
- The steep global decline in the price of investment is by and large an advanced-economy phenomenon.
  - Between 1993 and 2014 the relative price of investment declined by about 12 percent in advanced economies.
  - Between 1993 and 2014 the relative price of investment declined by about 7 percent in emerging market and developing economies as a whole.
- The milder overall decline in emerging market and developing economies is explained in large measure by the smaller weight of information and communications technology capital and machinery and equipment in their investment goods basket and the greater commodity intensity of their investment.
- Countries differ widely in their initial exposure to routinization, which exhibits a negative correlation with the subsequent change in labor shares of income.
  - Initial exposure to routinization is measured as the first available observation between 1990 and 1995.
- Advanced economies were more exposed to automation of routine tasks and experienced a larger fall in investment good prices than emerging market and developing economies, leading to greater substitution of capital for labor in advanced economies.

### Global Integration: Trade, Global Value Chains, and Capital Deepening
- Trade and financial integration are widely viewed as significant determinants of the evolution of labor shares.
- Several interrelated mechanisms—with potentially offsetting impacts—may be at play, and it is extremely difficult to quantify distinct effects of each driver.
- Trade integration theory: capital-abundant advanced economies may specialize in capital-intensive goods, triggering resource reallocation across sectors that lowers the labor share of income; the opposite is predicted for labor-abundant emerging market and developing economies.
- Participation in global value chains increased (measured as the sum of forward and backward linkages in vertical specialization).
  - Among advanced economies, this reflects offshoring of production of intermediate goods and, since the late 1990s, a steady increase in offshoring of services.
  - Among emerging market and developing economies, this reflects increased importation of components for assembly and re-exportation in global value chains.
- Mechanism sketched: expansion of global value chains, enabled by a collapse in communications and transportation costs, has allowed firms to unbundle production into tasks and exploit factor cost disparities; one such mechanism can account for a decline in labor shares in both advanced and emerging market and developing economies (details in Annex 3.2).
- Empirical relationship highlighted:
  - Change in log (capital stock/employment) relationships with change in log relative price of investment (sectoral and aggregate regressions reported):
    - Aggregate, Advanced Economies (Change between 1992 and 2013): Δ log (capital stock/employment) = 0.26*** – 0.93** Δ log(PI)
    - Aggregate, Emerging Market and Developing Economies (Change between 1992 and 2013): Δ log (capital stock/employment) = 0.48*** – 0.07 Δ log(PI)
    - Sectoral, Advanced Economies (Change between 1995 and 2007): Δ log (capital stock/employment) = 0.57*** – 0.40*** Δ log(PI)
  - Note: *** indicates 1 percent statistical significance; ** indicates 5 percent statistical significance.

### Interaction of Drivers and Measurement Issues
- The chapter divides main drivers into four broad categories: technological advancement; global integration; policies, institutions, and regulation of labor and product markets; and measurement issues.
- The separation of these drivers is artificial because they are potentially intertwined and mutually reinforcing.
  - Example: decline in corporate taxation rates may reflect intercountry competition to attract capital in a globalized world.
  - Declining unionization rates may reflect the decline of labor’s bargaining power, itself a result of trade integration.
- It is therefore extremely difficult to quantify the distinct effects of each of these drivers.

_International Monetary Fund | April 2017_

### CHAPTER 3

### CHAPTER 3

### Offshoring, Global Value Chains (GVCs), and Labor Income Shares
- Offshoring of relatively labor-intensive tasks from advanced economies to emerging market and developing economies can make production in advanced economies more capital-intensive and lower their labor income shares.
- Offshoring (or its threat) lowers labor’s bargaining power, further reducing the labor share within remaining tasks.
- Expansion of GVCs coincided with a steep decline in the relative price of investment goods in advanced economies, facilitating automation of more tasks. Tasks most likely to be automated are those for which labor is most substitutable by capital; tasks with low elasticity of substitution between capital and labor are most likely to be offshored.
- Key model insight: if offshored tasks have limited substitutability between capital and labor, participation in GVCs can reduce labor income shares in recipient emerging market and developing economies by shifting production toward tasks with higher capital shares.
- Elsby, Hobijn, and Şahin (2013) hypothesis: tasks that are labor-intensive in advanced economies may be capital-intensive relative to existing tasks in recipient economies, raising capital shares in both sending and receiving economies.
- Stylized evidence (Figure 3.8) suggests rising GVC participation is associated with rising capital intensity, particularly in emerging market and developing economies.
- Empirical associations (change between 1992 and 2013):
  - Advanced economies: Δ log (capital stock/employment) = 0.32*** + 1.19  Δ GVC participation
  - Emerging market and developing economies: Δ log (capital stock/employment) = 0.479*** + 2.71*  Δ GVC participation
- Note: Change in capital intensity refers to the change in log (capital stock/employment); change in GVC participation is measured using the backward linkage (share of foreign value added in gross exports). "***" indicates 1 percent statistical significance; "*" indicates 10 percent statistical significance.

### Financial Integration
- Two channels by which capital mobility can affect labor shares:
  - By facilitating relocation of production to countries with cheaper inputs, capital mobility lowers labor’s bargaining position.
  - By increasing access to capital, financial integration lowers the cost of capital in capital-scarce countries, facilitating capital deepening and greater substitution of capital for labor.
- The second channel may be especially relevant for emerging market and developing economies where financial frictions and credit rationing are more prevalent; benefits of financial integration may accrue largely to high-skilled workers who are more complementary with capital.
- Empirical and theoretical references cited: Kramarz (2016); Caselli and Feyrer (2007); Boz, Cubeddu and Obstfeld (2017).

### Policies, Institutions, and Regulations
- Labor and product market policies, institutions, and regulations influence labor shares:
  - Decline in corporate income tax rates can raise the relative return to capital, inducing substitution of capital for labor and lowering the labor share.
  - Trend decline in unionization rates may reflect lower bargaining power of labor (see Figure 3.6, panel 4), contributing to declines in labor income shares.
  - Changes in regulations governing hiring/dismissal or competition in product markets can affect factor shares through size and distribution of rents.
  - Market structure changes—possibly from technological advances and global product market integration—can increase industry concentration (“winner-take-most” dynamic) and raise profit shares, reducing labor shares (Autor and others (2017)).

### Measurement Issues
- Two important measurement challenges that could affect reported labor shares:
  - Labor income of the self-employed is imputed in national accounts; adjustments for self-employment would generally raise the level of the labor share.
  - Depreciation of capital arguably should be discarded from factor income shares because it cannot be consumed; adjustments for depreciation affect measured capital and labor shares.
- These measurement issues can affect trends:
  - Falling self-employment rates would make the measured decline in the labor share steeper.
  - Rising capital depreciation rates would make the measured decline less pronounced.
- This chapter treats measurement issues as an additional factor and reports robustness to different measures of the labor share (Figure 3.9, Box 3.4).
- Empirical note: Adjustment of the labor share for self-employment and capital depreciation results in level changes and changes in trend. The level shift from self-employment adjustment is larger in emerging markets and developing economies; capital depreciation adjustment is larger in advanced economies.

### Empirical Analysis: Shift-Share Decomposition and Long-Term Drivers
- Shift-share analysis sample and setup:
  - Sample: 27 advanced economies and 13 emerging market and developing economies across 10 one-digit industries (International Standard Industrial Classification).
  - Decomposition breaks trend changes in labor shares into within-industry and between-industry (reallocation) components.
  - Formula used for annual decomposition: △ LS_{i,t} = ∑_{k=1}^{n}(w_{i,k,t−1} △ LS_{i,k,t}) + ∑_{k=1}^{n}(△ w_{i,k,t} LS_{i,k,t−1}) (first sum = within; second = between), summed over years.
- Main shift-share findings:
  - Reallocation across broad industrial categories has generally not been a significant driver of labor share trends.
  - Most countries cluster around the 45-degree line: trend changes in labor shares emerge overwhelmingly from trend changes in within-industry labor shares rather than reallocation across industries.
  - The within component accounts for more than 90 percent of the total trend change (one-digit decomposition).
  - An important exception is China: reallocation from industries with relatively high labor shares (notably agriculture) to expanding industries with lower labor shares (wholesale trade; transportation and communication) accounts for some 60 percent of the total decline in the labor share during 1991–2014.
  - Similar findings at higher resolution: for 22 OECD economies using two-digit data covering 31 sectors, over 70 percent of variation is explained by within two-digit sector variation; between-sector reallocation often tended to increase labor shares in advanced economies.
- Interpretation:
  - These findings provide little support for traditional trade theory predictions (that structural shifts alone explain labor share declines) and suggest focusing on within-industry drivers—such as technology, GVC participation, financial integration, and policies—to understand overall labor share trends.
- Approach to analyzing long-term changes:
  - The empirical strategy emphasizes long-term changes in labor shares and long-term changes in potential drivers to capture structural adjustments and avoid bias from cyclical fluctuations.
  - Regressions allow capital and labor to adjust freely in response to changes in relative costs over the long term; controlling for the relative price of investment goods captures immediate demand effects and potential endogenous adjustments in factor supplies.

*Source: CHAPTER 3, International Monetary Fund | April 2017*

### CHAPTER 3

### CHAPTER 3

### Empirical model and estimation sample
- Sample limited to countries with at least 10 years of data over the 1991–2014 period: 49 countries (31 advanced economies and 18 emerging market economies).
- Technology proxied by the change in the relative price of investment goods, following Karabarbounis and Neiman (2014).
- Initial exposure to routinization measured at the start of the period to capture heterogeneous susceptibility to capital-labor substitution.
- Global integration measured using alternative indicators, including participation in global value chains and financial integration (robustness checks use measures such as intermediate imports excluding commodities, volumes of intermediate imports, and gross stocks of inward and outward foreign direct investment; additional robustness checks described in Annex 3.4).
- Labor and product market structure captured by changes in union density and corporate taxation rates (corporate tax rates measured using basic central government statutory (flat or top marginal) corporate income tax rates).
- Regressions include indicators for countries that enacted significant reforms in deregulating employment protections and product markets during 1991–2014.
- Technical details summarized in Annex 3.4.

### Aggregate findings and decomposition of labor share trends (1991–2014)
- The empirical model closely tracks changes in labor shares during 1991–2014 and explains about two-thirds of the evolution of aggregate labor share trends across countries.
- Notable outliers:
  - China: a significant change in industrial composition contributed to the decline in the labor share.
  - South Africa: a substantial increase in financial integration is the key contribution to the predicted rise in labor share, but much of the cross-border financial flows were driven by extractive industries.
- Technology:
  - A decline of 15 percent in the relative price of investment goods (the average decline in the sample) leads to:
    - a 0.4 percentage point decline in the labor share in a country with relatively low initial exposure to routinization.
    - about a 1.5 percentage point decline in a country with high exposure to routinization.
  - The finding that about half of the decline in labor shares is traceable to technology is consistent with Karabarbounis and Neiman (2014).
- Global value chain (GVC) participation:
  - Overall trade in goods and services does not appear to matter much for labor shares, but participation in global value chains does.
  - An increase in intermediate goods imports of 4 percent of GDP (corresponding to the median increase in GVC integration in the sample) is associated with a 1.6 percentage point decline in the aggregate labor share, on average, with a significantly larger impact in emerging markets.
  - In advanced economies, offshored tasks tend to be labor-intensive in source countries and can lead to reallocation of displaced workers to low-skill (labor-intensive) services, which may mitigate the negative impact of offshoring on labor shares.
- Financial integration:
  - Contrasting effects across country groups:
    - Advanced economies: financial integration depresses labor shares, consistent with rising capital mobility increasing the bargaining power of capital and facilitating relocation of production.
    - Emerging markets: financial integration raises labor shares, consistent with capital inflows lowering the cost of capital and—if the elasticity of substitution is lower than 1—raising the labor share; impact likely driven by raising the labor income share of high-skilled workers.
- Policy and institutional measures:
  - Measures of trend changes in labor and product market regulation, and changes in corporate taxation, are not found to have robust effects on labor share trends over the sample period.
  - Declines in corporate income taxation show a strong bivariate correlation with trend changes in labor shares, but are not statistically significant when controlling for globalization and technological progress.
- Decomposition (advanced economies, aggregate over 25 years):
  - Technology (declining relative price of investment goods and initial routinization exposure) accounts for almost half of the overall decline in labor shares.
  - Global integration (GVC participation and financial integration) contributes about half as much as technology.

### Heterogeneity across countries and groups
- Advanced economies:
  - Joint negative effect of technology and global integration explains roughly three-quarters of the decline in labor shares in Germany and Italy and more than half of the decline in the United States.
  - United Kingdom experienced a modest increase in labor share that does not conform to the general pattern.
  - Finland and Norway had low exposure to routinization and experienced trend increases in labor shares.
- Emerging markets and developing economies:
  - Global integration forces have large but partially offsetting effects: GVC participation lowers labor share while financial integration raises it.
  - Technology plays a very small role in the aggregate for emerging markets, but impacts are heterogeneous across countries.
  - Examples:
    - Brazil: the increase in the relative price of investment goods, together with financial integration, explain about half of the trend rise in labor share; GVC participation plays a negligible role.
    - Turkey: decline in labor share explained almost exclusively by rapid rise in GVC participation; technology plays a limited role given very low exposure to routinization.

### Sectoral analysis (country-sector level, 27 advanced economies)
- Sample restricted to 27 advanced economies with country-sector data for at least 10 years.
- Aggregate declines conceal substantial heterogeneity across industries; even within industries there are cross-country differences (e.g., manufacturing saw large average declines but labor shares fell in only about two-thirds of countries).
- Sectoral model incorporating trade and technology explains observed changes in labor shares reasonably well.
- Technology and routinization:
  - Declines in the relative price of investment are associated with declines in labor shares, more so for sectors with higher initial exposures to routinization.
  - Predicted large declines in labor shares for manufacturing, mining and quarrying, and transportation (high routinization sectors); predicted increases in agriculture and wholesale and retail trade (low routinization sectors).
  - The median decline in the price of investment (~15 percent over 25 years) predicts:
    - a 1.8 percentage point decline in the labor share of a country sector at the 25th percentile of the distribution of routinization.
    - an approximately 3.8 percentage point decline in the labor share of a country sector at the 75th percentile of the distribution of routinization.
  - The model predicts a 6 percentage point larger decline in labor shares in manufacturing (around the 75th percentile of routinization) than in restaurants and hotels (around the 25th percentile); this matches observed differences.
- Tradables vs. nontradables:
  - Increasing participation in GVCs is associated with declines in labor shares only in tradables sectors.
  - GVC participation does not have a statistically significant effect on nontradables sectors; model predictions for nontradables are ambiguous and depend on links to unbundled and offshored production processes.
- Unobserved sector-level trends:
  - Trends in technological advancement over-predict the overall decline in labor shares in advanced economies; unobserved sector-level trends have played an important counterbalancing role.

### Analysis by skill
- Sample for skill analysis dominated by advanced economies (aggregate analysis by skill focuses on 27 advanced economies and 10 emerging market economies).
- Purpose: examine distributional effects of drivers across skill levels (section introduces the approach; detailed skill-level results and numerical estimates are provided in Annex tables and figures referenced in the chapter).

*Source: CHAPTER 3, International Monetary Fund | April 2017*

### CHAPTER 3

### CHAPTER 3

### Skill-group labor share dynamics
- Sample: 27 advanced economies and 5 emerging market economies.
- The labor income share of high-skilled workers has been increasing while that of middle- and low-skilled workers has been declining.
- The rising skill premium could encourage upgrading of skills, raising relative supply of high-skilled labor and lowering relative supply of middle- and low-skilled labor; the chapter studies whether drivers beyond composition effects contributed to divergent evolution.
- Decomposition results (Figure 3.14) indicate:
  - Technological advancement and participation in global value chains have lowered the income share of middle-skilled workers.
  - These drivers have had little discernible effect on the labor income shares of low- or high-skilled workers.
- Countries with higher exposure to routinization and greater increases in participation in global value chains experienced stronger declines in the middle-skilled labor income share, especially Austria, Germany, and the United States.
- The stronger negative effect of global value chain participation over technology for the middle-skilled labor share is based on a sample that includes emerging market and developing economies; for an advanced-economy-only sample, technology plays a much larger role relative to global value chain participation.

### Sectoral exposure and mechanisms
- Because exposure to routine-biased technological progress differs across sectors, sector-level analysis was conducted:
  - Sectors more exposed to routine-biased technological progress experience stronger declines in middle-skilled labor income shares.
  - Measures of technological change have a stronger effect on the middle-skilled labor income share.
- Analysis distinguishing employment versus wage adjustment (using share of each skill group in total hours) finds:
  - The impact of technological advancement on the middle-skilled labor income share is very similar when controlling for skill composition, suggesting the decline occurred mostly through wage adjustment or relocation within broadly defined sectors.
- Results also exhibit capital-skill complementarity: the coefficient on the relative price of investment suggests low-skilled workers are more likely to be replaced by capital than middle- and high-skilled workers.

### Summary of empirical findings
- Global downward trend in the labor share of income since the early 1990s, with heterogeneity across countries, sectors, and skill groups.
- In the vast majority of economies, within-sector declines, rather than labor reallocation toward low-labor-share sectors, drove the overall decline in labor’s share of income.
- Dominant drivers:
  - Advanced economies: Technological progress has been the key driver, reflected in the steep decline in the relative price of investment goods, combined with high exposure to routine occupations that could be automated; global integration plays a smaller role.
  - Emerging markets (as a group): Evolution of labor shares is explained predominantly by global integration, with a more limited role for technology. This reflects a much less pronounced decline in the relative price of investment goods and lower exposure to routinization.
- The decline in the aggregate labor share in advanced economies occurs through a reduced share for middle-skilled labor, corroborating evidence that automation and import competition/offshoring have led to long-term losses in middle-skill occupations and displacement to lower-wage occupations.
- In emerging markets, global integration has been associated with capital deepening, rising wages and employment, and gains in living standards; the decline in labor share need not by itself call for policy intervention, but policies should aim to make access to opportunities and gains from growth more broadly shared.

### Policy implications and recommendations
- Policy responses should depend on country circumstances (levels of development, extent of decline in labor shares, relative importance of drivers, existing social safety nets).
- In advanced economies, prioritize policies to help workers cope with disruptions from technological progress and global integration, including:
  - Skill upgrading for affected workers.
  - Long-term investment in education and opportunities for skill upgrading throughout workers’ careers.
  - Policies facilitating reallocation of displaced workers to new jobs, reducing costs of job search and transitions.
  - Well-designed policies to support reemployment and reduce use (and cost) of income-support programs.
  - Where shocks are concentrated in specific regions, sectors, or skill/age groups, consider longer-term redistributive measures tailored to specific circumstances and anchored in each country’s social contract.
- In emerging markets and developing economies:
  - Promote skill deepening to prepare workers for further structural transformation and to facilitate income convergence.
  - Ensure policies work to make access to opportunities and gains from growth more broadly shared, anticipating potential future challenges as automation progresses.

### Historical perspective: Technological progress and labor shares
- Earlier episodes of rapid technological progress (Industrial Revolution) were accompanied by lower labor shares during phases when labor-saving technologies spread across the economy and affected particular groups and sectors disproportionately.
- Caveats: scarcity of data on labor shares for historical periods; often use inequality measures as proxies; disentangling drivers (technology, trade, labor scarcity, policies/institutions) is difficult for historical episodes.
- United Kingdom historical evidence:
  - Labor shares largely flat during the First Industrial Revolution (1760–1820/1840) when mechanization affected limited parts of the economy and increased demand for labor complementary to capital goods.
  - Profit and capital shares increased during 1850s–1870s as major labor-saving technologies spread (steam transportation, machine tools, factory machinery).
  - Labor shares initially increased during the Second Industrial Revolution (1870–1914) as profits fell during the Long Depression (1873–96).
  - Industrialization affected sectors and groups unevenly: domestic cottage industry workers bore much of the burden during 1820s–50s while factory wages rose.
  - Evidence of capital-skill complementarity and hollowing out of some occupations parallels modern patterns.
- Historical narrative shows recurring concerns about technological displacement of workers, distinguishing short-term dislocation from long-term effects.

*International Monetary Fund | April 2017*

### Box 3.1 (continued)

### Box 3.1 (continued)

### Historical effects of technological progress on labor shares and inequality
- Technological progress during various episodes of industrialization was associated with declines in labor shares during certain phases and for some groups of workers—and with increases in inequality.
- The level of inequality at its historical peak (typically around the late 19th to early 20th centuries in rich countries) was considerably higher than it is today.
- Adjustment to technological changes is argued to have taken about a generation (Lyons 1989).
- Keynes (1932) described technological unemployment as “only a temporary phase of maladjustment,” concluding that “in the long run that mankind is solving its economic problem.”
- A full comparison between the effects of technological progress on labor shares and inequality during the Industrial Revolution and more recent times is difficult because the rate of increase in inequality can be measured only from the first available data point, which varies between the 13th and 19th centuries, and because technological changes then and now are similarly difficult to quantify.

### The elasticity of substitution between capital and labor: concept
- The elasticity of substitution measures the extent to which firms can substitute capital for labor as the relative cost of the two factors changes; introduced by Hicks (1932) and Robinson (1933).
- In a Cobb-Douglas production function, the elasticity of substitution is equal to 1, implying a constant labor income share when relative factor costs change.
- If the production function takes a constant-elasticity-of-substitution form, the elasticity of substitution can be greater or less than 1; for example, if the elasticity of substitution is greater than 1, a decline in the relative cost of capital lowers the labor share.
- The elasticity of substitution need not be stable over time and could vary across industries and countries; it also depends on workers’ skills and the nature of tasks (routine and codifiable tasks are more substitutable).
- Examples: clerical and assembly-line work have high elasticity of substitution, whereas cutting hair and performing surgery are less prone to substitution.
- Mathematical definitions and functional forms in the source:
  - Elasticity of substitution: − ∂ ln (K/L) / ∂ ln (MPK/MPL) , (3.2.1)
  - Constant-elasticity-of-substitution production function:
    Y = A( α K^{1 − 1/ρ} + (1 − α) L^{1 − 1/ρ} )^{ρ/(ρ−1)} , (3.2.2)
  - MPK/MPL = (K/L)^{−1/ρ} , (3.2.3)
  - By definition, the elasticity of substitution is exactly ρ. When ρ = 1, the function reduces to Cobb-Douglas: Y = A K^{α} L^{1−α}.

### Empirical evidence on heterogeneity of the elasticity of substitution
- Cross-country regressions estimate country-level elasticity of substitution separately for advanced and emerging market and developing economies by regressing long-term changes (over at least eight years) in labor shares on long-term changes in the log of the relative price of investment goods for each country.
  - Reduced-form equation: ˆLS_c = α + β ˆPI_c + ε_c . An elasticity of substitution greater than 1 implies β > 0; less than 1 implies β < 0.
- Results (illustrated in Figure 3.2.1):
  - For advanced economies: estimated elasticity of substitution is greater than 1 (panel 1: positive slope coefficient statistically significant at the 5 percent level).
  - For emerging market and developing economies: estimated elasticity of substitution is less than 1 (panel 2: negative slope coefficient statistically significant at the 10 percent level).
- One explanation for higher aggregate elasticity of substitution in advanced economies is greater exposure to routinization, evidenced by a higher aggregate routine task intensity (RTI) in advanced economies.
- Using routinization scores by occupation aggregated with employment shares yields a distribution of aggregate RTI:
  - The distribution of the RTI index for advanced economies has a higher mean and median and is less dispersed than for the emerging market group (Figure 3.2.2).
- The chapter’s key finding supported by these estimates: declines in the relative cost of capital have played a more prominent role for labor share declines in advanced than in emerging market economies.

### Industry-level elasticity and routinization
- Industry-specific elasticity of substitution is estimated by regressing changes in labor income shares on changes in the relative price of investment in two-digit industries using World Input-Output Database data.
- Estimated elasticity of substitution is lowest in agriculture and accommodation and food services and highest in construction, transportation, and wholesale trade (Figure 3.2.3).
- There is a strong correlation between sector estimated elasticity of substitution and the sector’s average degree of routinization (sector-specific RTI index averaged across countries).
  - Agriculture yields the lowest RTI index across countries.
  - Construction and transportation have among the highest RTI indices and estimated elasticity of substitution (Figure 3.2.4).
- Given advanced economies’ lower employment share in agriculture and higher shares in construction and transportation relative to emerging market and developing economies, these industry patterns are consistent with advanced economies’ higher exposure to routinization.

### Routine tasks, automation, and global exposures
- The real cost of computing power fell at a rate of more than 50 percent annually between 1969 and 2005 (Nordhaus 2007).
- Routine tasks (Autor, Levy, and Murnane 2003) are defined as those which “. . . require methodical repetition of an unwavering procedure . . . exhaustively specified with programmed instructions and performed by machines.”
- Routinization—the automation of routine tasks—has been identified as an important cause of displacement and stagnant wage growth of middle-skilled labor in many advanced economies.
- Magnitude of dislocations varies significantly across countries; possible reasons include differences in intensity of routine occupations, different automation rates, and idiosyncratic factors such as industrial composition.
- Construction of RTI-based measures:
  - Start with scores for 330 occupations at the three-digit level from Autor and Dorn (2013), ordered by routinizability.
  - Map the 330 occupation-level scores into nine aggregate one-digit occupation categories based on the 1988 International Standard Classification of Occupations.
  - Standardize aggregated one-digit occupation scores to mean zero and standard deviation one.
  - Aggregate country- and industry-level routine exposures by weighting occupation-category RTI scores with occupation employment shares:
    - RTI_jit = Σ_l ω_ljit × RTI_l ; RTI_it = Σ_l ω_lit × RTI_l  , (3.3.1)
    - where ω_ljit and ω_lit are occupation l’s share of employment in industry j, country i, at time t, and occupation l’s share of employment in country i at time t, respectively.
- Data coverage and frequency:
  - Employment data from population censuses and labor force surveys are used to construct routine exposures for all years with such surveys.
  - Between 1990 and 2015, this yields time-varying exposures to routinization for 160 countries at annual, biennial, quinquennial, or decennial frequencies.
  - Exposures are generally available at annual frequency for many advanced economies; frequencies are lower for most emerging market and developing economies.
  - Industry-level routine exposures are available for a slightly smaller subset of years and countries than economy-level metrics due to industry-affiliation reporting limitations.
- Stylized facts from aggregate routine exposure metrics:
  - Initial exposures to routinization vary across industries and differ somewhat between country income groups.
    - Agriculture is least exposed; accommodation and health services are also relatively low; exposure is highest in manufacturing and transportation.
  - Routine exposures are highest in advanced economies but have been converging across country income groups over time.
    - Advanced-economy exposures have declined over time, while exposures in emerging market and developing economies have risen steadily, resulting in convergence in worldwide routine exposures.
  - The initial exposure to routinization is a powerful predictor of subsequent change in exposure:
    - In advanced economies, the higher the initial exposure to routinization, the larger its subsequent decline.
- Specific measured values and ranges:
  - Routine exposure of agriculture is very similar in all country groups and over time, between −1.15 and −1.2.
  - Value added for agriculture was 2 percent of GDP or less in advanced economies as a whole between 1990 and 2014, and ranged from 13 to 20 percent in emerging market and developing economies as a whole during that period.

*Source: Box 3.1 (continued); Box 3.2; Box 3.3 — WORLD ECONOMIC OUTLOOK: GAINING MOMENTUM? International Monetary Fund | April 2017*

### Box 3.3 (continued)

### Box 3.3 (continued)

### Evolution of Routine Exposure and Structural Transformation
- Finding: Where initial exposure was higher, through more intensive displacement of labor with capital, marginal tasks became less routine in advanced economies; in emerging market and developing economies, however, the higher the initial exposure to routinization, the smaller the subsequent rise in exposure.
- Interpretation: Forces that plausibly lower exposure to routinization—such as the declining relative price of investment and subsequent substitution of labor with capital—have been weaker in emerging market economies than forces that raise routine exposure—such as structural transformation.
- Finding: Structural transformation appears to be a key driver of the evolution of routine exposures. As emerging market and developing economies have transitioned from agriculture to manufacturing and services (sectors that have generally more routine occupations), their routine exposure has risen. Advanced economies are at a different stage of structural transformation.
- Empirical evidence referenced: Figures 3.3.2, 3.3.3, and 3.3.4 document routine exposure across country groups and over time (1990–2015), the relationship between initial routine exposure and subsequent change (1990–2015), and the link between structural transformation (change in agriculture VA / (manufacturing VA + services VA)) and change in routine exposure (1990–2015).

### Measurement Issues in Labor Shares: Overview
- Context: Since the 1990s the labor share of income has decreased in the majority of advanced economies and in a number of emerging market and developing economies.
- Purpose of box: Discuss the extent to which measurement issues—particularly the statistical treatment of self-employment and capital depreciation—may account for some observed labor share patterns.
- Authors of the box: Jihad Dagher and Benjamin Hilgenstock.

### Unadjusted Labor Share (definition)
- Definition (equation 3.4.1): LS_U = compensation of employees / gross domestic product (GDP)
- Note: In most national accounts, compensation of employees captures only payroll employees and thus ignores labor income of self-employed people; the unadjusted labor share is also called the payroll share or the “naive” labor share.
- Implication: By disregarding self-employment, the unadjusted measure may underestimate the level of the labor share and may fail to reflect structural changes over time (for example, a declining share of self-employment as countries develop can bias levels downward and trends upward).

### Adjustment for Self-Employment
- Two common approaches:
  - Assume the labor share of the self-employed equals the labor share in the payroll sector (compensation of employees divided by value added of the payroll sector).
  - Assume the self-employed earn, on average, the same compensation as payroll employees.
- Adjustment formula (equation 3.4.2) discussed (Gollin 2002):
  - LS_SE = (1 + L_S / L_P) × LS_U
    - where L_S and L_P represent the number of self-employed people and payroll employees, respectively.
- Empirical illustration: Panel 1 of Figure 3.4.1 compares the self-employment-adjusted labor share with the unadjusted measure in the United States, 1948–2016. The decline in the adjusted measure is more pronounced than in the unadjusted labor share because of the trend decline in the share of the self-employed; nonetheless, both indicate a steady decline in the United States since the early 1970s.

### Adjustment for Capital Depreciation
- Rationale: Depreciation cannot be consumed and therefore should not be attributed to either capital or labor income.
- Adjustment formula (equation 3.4.3):
  - LS_D = compensation of employees / (GDP − depreciation)
- Empirical note: Capital depreciation has increased over time in the United States due to the growing weight of information, communications, and technology capital, which depreciates faster than other types of capital. Panel 2 of Figure 3.4.1 shows that after adjustment for depreciation the trend in the labor share is less steep, though it remains negative.

### Effects of Adjustments across Countries
- Finding: Applying adjustments for self-employment and depreciation can have a substantial impact on labor share developments.
- Empirical evidence:
  - Figure 3.4.2 shows impacts for four large advanced economies (1980–2014).
  - Figure 3.4.3 shows the effect of adjusting for self-employment and capital depreciation on long-term trends in the labor share for 12 advanced economies and 12 emerging market and developing economies (long changes reported in units per 10 years).
  - Figure 3.4.4 shows trends in self-employment and depreciation (long changes, 1991–2014).
- Patterns:
  - In almost all cases, adjusting for self-employment makes the labor share decline steeper, particularly in emerging market and developing economies.
  - Adjusting for capital depreciation tends to flatten the labor share, primarily in advanced economies because of their higher share of information, communications, and technology in total capital.
- Methodological note: Unadjusted labor shares are used in the chapter’s empirical analysis due to data limitations, but key findings are robust to using adjusted measures (as illustrated in Annex Table 3.5.5).

### Annex 3.1 — Wages and Deflators
- Conceptual distinction:
  - Real (consumption) wage: nominal wage deflated by the consumer price index (CPI); reflects workers’ purchasing power and is relevant for welfare and political economy implications.
  - Product wage: nominal wage deflated by the GDP deflator; affects firms’ hiring incentives and is appropriate for comparisons with productivity when examining the functional distribution of GDP.
- Importance for open economies: Changes in the terms of trade (for example, an increase in the price of an imported good such as oil) can raise the CPI relative to an output price index; consumption wages may thus appear to fall relative to productivity even if the decline is driven only by differences in deflators.
- Empirical result: Wage growth has been lagging productivity growth. Annex Figure 3.1.1 decomposes changes in average labor productivity and changes in wages deflated by the GDP deflator and by the CPI; Annex Figure 3.1.2 shows evolution of product wages, consumption wages, and average labor productivity in manufacturing for advanced economies.
- Overall pattern: On average, consumption wages have increased less than product wages, and both have lagged productivity.

### Annex 3.2 — Theoretical Model: Relative Cost of Capital, Offshoring, and Labor Shares
- Purpose: Develop a theoretical model showing how a fall in the relative cost of capital may influence offshoring and its impact on labor shares in advanced and emerging market and developing economies.
- Motivation: Strong expansion of global value chains since the 1990s coincided with a rapid fall in the relative cost of capital in advanced economies. Three important drivers of the cost of capital—the price of investment goods, the interest rate, and the corporate income tax—have declined substantially during this period.
- Mechanism highlighted:
  - Advanced economies: Offshored tasks are relatively labor intensive; automation and offshoring lead the remaining domestic production to be more capital intensive, lowering labor income shares.
  - Emerging market economies: A steep decline in the relative cost of capital in advanced economies leads firms there to automate tasks that can be easily automated and to offshore tasks that cannot. Because the relative cost of capital is comparatively high in emerging market economies (capital scarcity), offshored tasks—often with low substitutability between capital and labor—tend to have higher capital shares than existing tasks, shifting composition toward higher capital shares and lowering aggregate labor income share.
- Clarification: The model does not assert that offshoring is caused mainly by a decline in the relative cost of capital; rather, it highlights a mechanism that can help explain simultaneous declines in labor shares in both country groups.
- References and further notes: The mechanism and related hypotheses are connected to Elsby, Hobijn, and Şahin (2013); Cho (2016); and discussion of elasticity of substitution (see Box 3.2). The depreciation rate of capital may have risen due to a larger share of software in capital (Eden and Gaggl 2015), but this is unlikely to offset other drivers’ decline.

*Source: Box 3.3 (continued) and Box 3.4 (Adjustments to the Labor Share of Income), Annex 3.1, and Annex 3.2 from the provided IMF text.*

### Annex Figure 3.1.2.  Product Wages, Consumption Wages,

### Annex Figure 3.1.2.  Product Wages, Consumption Wages, and Productivity in Manufacturing (Index, 1991 = 1)

### Key empirical figure description
- The figure presents indexed series (1991 = 1) for:
  - Advanced Economies (panel 1)
  - United States (panel 2)
  - Germany (panel 3)
  - Portugal (panel 4)
- Plotted series in each panel: Productivity; Product wages; Consumption wages.
- Horizontal axis labels shown: 1991 95 2000 05 10 14.
- Vertical axis numeric ticks shown: 0.5, 1.0, 1.5, 2.0, 2.5.

### Theoretical mechanism and model setup
- Production function for a task parameterized by α and ρ (constant elasticity of substitution):
  - ( α K^(1−1/ρ) + (1 − α) L^(1−1/ρ) )^(ρ/(ρ−1)). (Equation (3.1))
- Cost of producing one unit of task {α, ρ}:
  - c(r, w; α, ρ) = ( α^ρ r^(1−ρ) + (1 − α)^ρ w^(1−ρ) )^(1/(1−ρ)). (Equation (3.2))
  - r denotes the cost of capital; w denotes the wage.
- Labor income share of a task {α, ρ}:
  - LS = 1 / [ 1 + α^ρ (1 − α)^(−ρ) (r/w)^(1−ρ) ]. (Equation (3.3))
- Partial derivative of LS with respect to (r/w):
  - ∂LS/∂(r/w) = (ρ − 1) α^ρ (1 − α)^(−ρ) (r/w)^(−ρ) / [ (1 + α^ρ (1 − α)^(−ρ) (r/w)^(1−ρ) )^2 ]. (Equation (3.4))
- Key implication from the algebra:
  - "a fall in the relative cost of capital r/w leads to a decline in the labor income share if and only if the elasticity of substitution ρ is larger than 1."

### Offshoring framework and characterization of offshored tasks
- Cost of producing a unit of task in the low-wage country (incorporating offshoring costs τ and w′ < w):
  - (1 + τ) c(r, w′; α, ρ) = (1 + τ) ( α^ρ r^(1−ρ) + (1 − α)^ρ w′^(1−ρ) )^(1/(1−ρ)).
- Set of tasks A that are offshored from high-wage to low-wage country:
  - A ≜ { (α, ρ, τ) : c(r, w; α, ρ) > (1 + τ) c(r, w′; α, ρ) }. (Equation (3.5))
- Log recharacterization of A:
  - A ≜ { (α, ρ, τ) : ∫_{w′}^{w} [ ∂ lnc(r, z; α, ρ) / ∂ z ] dz > ln(1 + τ) }. (Equation (3.6))
- Assumption: cost of capital r is the same across high- and low-wage countries (motivated by foreign direct investment and capital mobility).

### Comparative statics on how changes in the cost of capital affect the composition of offshored tasks
- Proposition 1:
  - "A decline in the cost of capital causes more tasks with ρ < 1 and fewer tasks with ρ > 1 to be offshored from the high-wage country to the low-wage country."
- Supporting algebra:
  - ∂^2 lnc(r, w; α, ρ) / ∂w ∂r = (ρ − 1) r^(ρ−2) w^(−ρ) ( (1 − α)/α )^ρ / [ 1 + ((1 − α)/α)^ρ (w/r)^(1−ρ) ]^2. (Equation (3.7))
  - Sign result:
    - ∂^2 lnc(r, w; α, ρ) / ∂w ∂r { > 0 if ρ > 1; < 0 if ρ < 1 }. (Equation (3.8))
  - Consequence when r declines from r1 to r2 < r1:
    - For any ρ > 1: ∫_{w′}^{w} ∂ lnc(r2, z; α, ρ)/∂z dz < ∫_{w′}^{w} ∂ lnc(r1, z; α, ρ)/∂z dz.
    - For any ρ < 1: ∫_{w′}^{w} ∂ lnc(r2, z; α, ρ)/∂z dz > ∫_{w′}^{w} ∂ lnc(r1, z; α, ρ)/∂z dz. (Equation (3.9))
  - Interpretation: decline in r expands the set of offshored tasks with ρ < 1 and contracts the set with ρ > 1.

### Combined effects of declines in cost of capital and offshoring costs
- Decline in offshoring cost τ:
  - Definition (3.6) implies a decline in τ causes more tasks to be offshored regardless of ρ.
- Interaction:
  - Declines in r and τ have conflicting effects for ρ > 1 and reinforcing effects for ρ < 1.
  - Net effect: tasks with ρ < 1 are more likely to be offshored when both r and τ decline.
- Illustration: Annex Figure 3.2.1 demonstrates panels for:
  - 1. Initial State (r0, τ0)
  - 2. Decline in the Cost of Capital (r1, τ0) with r0 > r1
  - 3. Further Decline in the Cost of Offshoring (r1, τ1) with τ0 > τ1
  - Note in figure caption: "This figure suggests that tasks with ρ < 1 are more likely to be offshored than tasks with ρ > 1 if there are declines in the cost of capital and the cost of offshoring."

### Implications for labor income shares
- Special-case illustration (Leontief offshorable tasks, Cobb-Douglas non-offshorable tasks; consumers with log preferences):
  - Leontief for task a: F(K, L) = min{K/a, L} implies zero elasticity of substitution.
  - Labor income share for task a:
    - wL / F(K, L) = wL / (wL + r(aL)) = 1 / (1 + a (r/w)). (Equation (3.10))
  - Any task a offshored satisfies a < a*, where:
    - a* = ( w − (1 + τ) w′ ) / ( τ r ).
  - Since labor income share is declining in a, offshoring removes lower-a tasks and leaves remaining tasks more capital intensive, reducing the labor income share in the high-wage country.
- Proposition 2:
  - "If the average labor income share of offshorable tasks is the same as that of non-offshorable tasks, offshoring because of a decline in the costs of capital and offshoring can reduce the labor income share in the high-wage country."
- Global effect:
  - Log preference ensures constant expenditure shares across tasks, so a decline in labor income share within offshored tasks implies offshoring will drive down the global labor income share.
- Effects in low-wage country:
  - Offshoring can reduce the labor income share in the low-wage country if offshored tasks predominantly have low elasticity of substitution and the average labor income share of tasks with ρ < 1 is substantially lower than that of tasks with ρ ≥ 1.
  - Additional consideration: capital scarcity and credit rationing in emerging market and developing economies may limit access to capital, reinforcing potential reductions in labor income share in low-wage countries.

### Data, country coverage, and empirical methodology (annex material)
- Country samples:
  - Aggregate long-term analysis: 31 advanced economies and 18 emerging market economies (countries listed in Annex Table 3.3.1).
  - Sectoral analysis: 27 advanced economies.
  - Skill-based samples: aggregate — 27 advanced economies and 10 emerging market economies; sectoral — 27 advanced economies and 5 emerging market economies.
- Data sources:
  - Labor Share (aggregate): Karabarbounis and Neiman (2014); national authorities; Organisation for Economic Co-operation and Development.
  - Labor Share (sectoral): CEIC database; EU KLEMS database; Organisation for Economic Co-operation and Development.
  - Labor Share by Skill: World Input-Output Database, Socio Economic Accounts, Release of July 2014.
  - Price of Investment: IMF, World Economic Outlook database.
  - Intermediate Imports and Global Value Chain measures: EORA MRIO database; World Input-Output Database; IMF staff calculations.
  - Routinization measures: Autor and Dorn (2014); Eurostat; IPUMS; ILO; national authorities; United Nations.
  - Other data: Penn World Tables 9.0; World Bank WDI; United Nations Industrial Development Organization; United Nations Comtrade; etc. (see Annex Table 3.3.2.)
- Aggregate regression baseline equation (long-term annualized changes during 1991–2014; hat variables denote changes):
  - ˆLS_c = α + β2 ˆPI_c + [ β3 RTI_0,c + β4 RTI_0,c ˆPI_c ] + β1 ˆ′G_c + β5 ˆ′Pol_c + ε_c. (Equation (3.11))
  - PI denotes the relative price of investment (relative to consumption) goods.
  - RTI_0 denotes initial exposure to routinization.
  - G includes globalization variables: changes in total goods trade (value-added exports and non-oil imports in percent of GDP), trade in intermediate goods, global value chain participation (forward and backward linkages or imported intermediate inputs in percent of gross value added), and changes in financial globalization (external assets and liabilities, excluding international reserves in percent of GDP).
  - Pol summarizes policy and institutional factors: changes in union density, corporate taxation, employment protection legislation, and product market reforms.
- Labor and product market reform indicators:
  - Developed using Fraser Institute’s Economic Freedom of the World data set ("hiring and firing regulations" and "business regulations") between 1995 and 2014.
  - Major deregulations assigned value 1 when change > country-specific mean + 1 standard deviation; major regulations assigned −1 when change < country-specific mean − 1 standard deviation; otherwise zero.

*Source: IMF staff compilation, World Economic Outlook: Gaining Momentum? April 2017.*

### Annex Figure 3.4.1.  Estimated Trends in Labor Shares across the World

### Annex Figure 3.4.1.  Estimated Trends in Labor Shares across the World

### Map and coverage
- World map displays labor share trend of countries with at least 10 years of data, starting in 1991.
- Legend categories (percentage points per 10 years): Less than –2; –2 to 0; 0 to 1; More than 1; No data.
- Sources: National authorities; and IMF staff calculations.

### Aggregate analysis — baseline cross-sectional results (Annex Table 3.5.1)
- Number of Observations: 49 (column 6, joint specification).
- R-squared: 0.636 (column 6).
- Selected coefficients (column 6, standard errors in parentheses):
  - Relative PI * Initial Routinization: 0.524*** (0.124)
  - Relative PI: 0.183** (0.0734)
  - Financial Integration: 1.72* (0.895)
  - Global Value Chain Participation: −0.574*** (0.0962)
  - Corporate Taxation: 0.0170 (0.0316)
  - AE dummy: −0.00117 (0.000820)
- Note: All variables (except initial routinization) are expressed as long-term changes. Here and elsewhere, the long-term change in financial integration (measured as the sum of external assets and liabilities in percent of domestic GDP) is divided by 100.

### Aggregate analysis — stacked-differences (Annex Table 3.5.2)
- Regression stacked over nonoverlapping five-year periods (t = 1992–96, 1997–2001, 2002–06, 2007–11).
- Number of Observations: 153 (column 6, robust regression with fixed effects).
- R-squared: 0.834 (column 6).
- Selected coefficients (column 6, standard errors in parentheses):
  - Initial Routinization: −0.0293*** (0.00459)
  - Relative PI * Initial Routinization: 0.273** (0.116)
  - Relative PI: 0.0223 (0.0350)
  - Global Value Chain Participation: −0.131** (0.0628)
  - Financial Integration: 0.0784 (0.0568)
  - Corporate Taxation: 0.127*** (0.0425)
- Interpretation notes from text:
  - Stacked-differences confirm baseline findings; technology effects similar in magnitude but less precisely estimated.
  - Global value chain participation effect is similar to trend results, implying faster adjustment to globalization than to technology.
  - Employment protection legislation reforms have a statistically significantly negative effect on labor shares within five years of the reform, but are dominated by technology and trade when jointly specified.

### Robustness checks — user cost, offshoring, measurement, and other checks
- User cost of capital (Annex Table 3.5.3.A):
  - Number of Observations: up to 49 (columns vary).
  - R-squared examples: 0.492 (column 1 baseline), 0.478 (column 4).
  - Relative PI * Initial Routinization: 0.285*** (0.0743) in column 1; 0.220*** (0.0702) in column 2.
  - Global Value Chain Participation: −0.166** (0.0653) in column 1.
  - Private Credit/GDP (trend) coefficient: 0.0290* (0.0154) where included.
  - Note: Comprehensive UCC affects labor shares similarly to price of investment, though less significant; accounting for general financial deepening can raise the labor share in emerging market economies.
- Alternative offshoring measures (Annex Table 3.5.3.B):
  - Number of Observations: 48–49 depending on column.
  - R-squared examples: 0.417, 0.470, 0.335, 0.400 across columns.
  - Imported intermediate inputs/GDP (Intermediate Goods Trade): −0.499*** (0.161) in column 1.
  - Relative PI * Initial Routinization: 0.261*** (0.0879) in column 1; similar positive interaction across columns.
  - Financial Integration: −0.160** (0.0604) in column 1.
  - Findings: Globalization in intermediate trade negatively affected labor shares across alternative definitions of offshoring.
- Measurement-adjusted labor shares (Annex Table 3.5.5):
  - Number of Observations: 48–49 depending on adjustment.
  - R-squared examples: 0.448 (baseline), 0.362 (self-employment-adjusted), 0.339 (depreciation-adjusted), 0.377 (self-employment- and depreciation-adjusted).
  - Relative PI * Initial Routinization remains positive and often statistically significant (e.g., 0.247*** (0.0779) baseline; 0.460* (0.264) self-employment-adjusted).
  - Global Value Chain Participation remains negative and significant across adjustments (e.g., −0.253*** (0.0796) baseline; −0.617** (0.252) self-employment-adjusted).
- Additional robustness (Annex Table 3.5.4):
  - Number of Observations ranges 25–50 across specifications.
  - R-squared examples: 0.357 (robust regression), 0.425 (GDP weighted), 0.584 (AEs, No Transition Countries), 0.581 (additional controls), 0.338 (without global financial crisis).
  - Relative PI * Initial Routinization robustly positive and often highly significant (examples: 0.235*** (0.0835), 0.335** (0.132), 0.923** (0.430)).
  - Global Value Chain Participation robustly negative across many specifications (e.g., −0.235*** (0.0809), −0.282** (0.120), −0.384*** (0.0664)).

### Sectoral analysis (Annex Table 3.5.6)
- Sample and fit:
  - Number of Observations: 9,237.
  - R-squared: 0.356 for Tradables Sectors; 0.173 for Nontradables Sectors.
- Tradables sectors (coefficients and standard errors):
  - Relative PI: 0.000412 (0.000279)
  - Initial Routinization: −0.00598** (0.00256)
  - Relative PI * Initial Routinization: −0.0000989 (0.000488)
  - Trade Integration: −0.000673** (0.000292)
  - Financial Integration: 0.00356 (0.0100)
  - Global Value Chain Participation: −0.00220** (0.000857)
- Nontradables sectors (coefficients and standard errors):
  - Relative PI: −0.00167*** (0.000491)
  - Initial Routinization: −0.00584 (0.00879)
  - Relative PI * Initial Routinization: 0.00486** (0.00181)
  - Trade Integration: −0.0000691 (0.000122)
  - Financial Integration: 0.0267 (0.0180)
  - Global Value Chain Participation: 0.00171 (0.00279)
- Interpretation: Results highlight differences between tradables and nontradables sectors; routinization and global value chain participation show sectorally heterogeneous relationships with labor shares.

### Analysis by skill
- Labor compensation by skill constructed using World Input-Output Database skill-level labor compensation as percent of total labor compensation, multiplied by labor compensation data at country and sector levels.
- Labor share by skill computed as ratio of labor compensation by skill to value added.
- Analysis conducted at aggregate and sectoral levels; results consistent and robust across exercises.
- Caveats noted:
  - Sectoral analysis sample predominantly advanced economies.
  - Larger measurement errors at sectoral level for price of investment and intermediate goods.
  - Greater factor mobility across sectors than across countries may imply different mechanisms in cross-country vs. within-country cross-sectoral analyses.

_Italic: Source — International Monetary Fund staff calculations; map and tables from Annex Figure 3.4.1 and Annex Tables 3.5.1–3.5.6 in the referenced chapter._

### Annex 3.3; for a detailed description of the estimation strategy, see Annex

### Annex 3.3

### Definitions and methodology
- Tradables sectors include agriculture, mining and quarrying, manufacturing, wholesale and retail trade, and transportation. Nontradables sectors include construction, finance, real estate, government, and community.
- All variables (except for initial routinization) are expressed as long-term trend changes.
- Trade integration = value added exports plus imports as a share of gross output.
- Robust standard errors are clustered at the country level.
- PI = price of investment.
- Significance notation: *** p < 0.01, ** p < 0.05, * p < 0.1.

### Annex Table 3.5.7 — Aggregate results by skill level (key coefficients and statistics)
- Sample sizes and fit:
  - Number of Observations: 37 (High Skilled), 37 (Middle Skilled), 37 (Low Skilled)
  - R 2: 0.299 (High Skilled), 0.351 (Middle Skilled), 0.047 (Low Skilled)
- Technology
  - Relative PI:
    - High Skilled: 0.0317 (0.0338)
    - Middle Skilled: 0.224** (0.104)
    - Low Skilled: −0.0293 (0.0686)
  - Initial Routinization:
    - High Skilled: −0.0011 (0.00110)
    - Middle Skilled: 0.002 (0.00263)
    - Low Skilled: −0.0001 (0.00187)
  - Relative PI * Initial Routinization:
    - High Skilled: 0.0460 (0.0616)
    - Middle Skilled: 0.408** (0.169)
    - Low Skilled: −0.104 (0.146)
- Global integration
  - Global Value Chain Participation:
    - High Skilled: 0.0315 (0.0989)
    - Middle Skilled: −0.811** (0.354)
    - Low Skilled: −0.100 (0.187)
  - Financial Integration:
    - High Skilled: 0.839*** (0.266)
    - Middle Skilled: −0.195 (0.301)
    - Low Skilled: −0.316 (0.339)
- Policies and institutions
  - Corporate Taxation:
    - High Skilled: 0.0268 (0.0576)
    - Middle Skilled: −0.237 (0.151)
    - Low Skilled: −0.0701 (0.0847)
  - Relative Skill Supply:
    - High Skilled: 0.666** (0.308)
    - Middle Skilled: 1.738 (1.545)
    - Low Skilled: −0.156 (2.152)

### Annex Table 3.5.8 — Sectoral results by skill level (selected coefficients, columns (1)–(6))
- Sample sizes and fit:
  - Number of Observations: 289 (columns 1–2), 297 (columns 3–4), 275 (columns 5–6)
  - R 2: 0.143, 0.381, 0.201, 0.435, 0.059, 0.214 (corresponding to columns (1)–(6))
- Technology (by column)
  - Relative PI:
    - (1) −0.00778 (0.0113)
    - (2) 0.0152 (0.0124)
    - (3) −0.0276 (0.0198)
    - (4) −0.0143 (0.0215)
    - (5) 0.0152 (0.0254)
    - (6) 0.0337 (0.0306)
  - Initial Routinization:
    - (1) −0.00134 (0.00144)
    - (2) −0.00233 (0.00144)
    - (3) 0.00118 (0.00256)
    - (4) 0.000386 (0.00252)
    - (5) −0.00216 (0.00314)
    - (6) −0.00223 (0.00339)
  - Relative PI * Initial Routinization:
    - (1) 0.0147 (0.0233)
    - (2) 0.0142 (0.0217)
    - (3) 0.0755* (0.0405)
    - (4) 0.0795** (0.0376)
    - (5) −0.0390 (0.0481)
    - (6) −0.0235 (0.0488)
- Global Value Chain Participation:
  - (1) 1.70e-05 (0.00210)
  - (2) 0.000152 (0.00207)
  - (3) 0.00430 (0.00329)
  - (4) 0.00117 (0.00326)
  - (5) −0.00144 (0.00399)
  - (6) −0.00125 (0.00425)
- Fixed effects:
  - Country Fixed Effects: Y in all columns shown
  - Sector Fixed Effects: N in columns (1), (3), (5); Y in columns (2), (4), (6)

### Annex Table 3.5.9 — Sectoral results by skill level, controlling for skill composition
- Sample sizes and fit:
  - Number of Observations: 289 (High Skilled), 297 (Middle Skilled), 275 (Low Skilled)
  - R 2: 0.506 (High Skilled), 0.564 (Middle Skilled), 0.329 (Low Skilled)
- Technology
  - Relative PI:
    - High Skilled: 0.00345 (0.0112)
    - Middle Skilled: 0.00147 (0.0190)
    - Low Skilled: 0.0393 (0.0284)
  - Initial Routinization:
    - High Skilled: −0.00144 (0.00129)
    - Middle Skilled: 0.000979 (0.00222)
    - Low Skilled: −0.00378 (0.00315)
  - Relative PI * Initial Routinization:
    - High Skilled: 0.0271 (0.0195)
    - Middle Skilled: 0.0649* (0.0331)
    - Low Skilled: −0.0404 (0.0452)
- Global integration
  - Global Value Chain Participation:
    - High Skilled: −0.00864 (0.0152)
    - Middle Skilled: −0.000356 (0.0265)
    - Low Skilled: −0.0108 (0.0361)
- Skill composition
  - Skill Share in Total Hours:
    - High Skilled: 0.511*** (0.0650)
    - Middle Skilled: 0.733*** (0.0846)
    - Low Skilled: 0.712*** (0.114)
- Fixed effects:
  - Country Fixed Effects: YYY
  - Sector Fixed Effects: YYY

### Annex Table 3.5.10 — Sectoral results by skill level, controlling for policy and institution variables (columns (1)–(6))
- Sample sizes and fit:
  - Number of Observations: 373, 382, 357, 357, 365, 342 (columns (1)–(6))
  - R 2: 0.164, 0.120, 0.050, 0.214, 0.237, 0.069 (columns (1)–(6))
- Technology (selected)
  - Relative PI:
    - (1) −0.00369 (0.0113)
    - (2) −0.0209 (0.0198)
    - (3) 0.00140 (0.0259)
  - Initial Routinization:
    - (1) −0.00189 (0.00140)
    - (2) 0.000193 (0.00249)
    - (3) −0.00111 (0.00315)
  - Relative PI * Initial Routinization:
    - (1) 0.00793 (0.0226)
    - (2) 0.0659* (0.0392)
    - (3) −0.0303 (0.0480)
- Global integration
  - Global Value Chain Participation:
    - (1) −0.00237 (0.0171)
    - (2) −0.0187 (0.0307)
    - (3) 0.00372 (0.0376)
  - Financial Integration:
    - (1) 0.805*** (0.182)
    - (2) 1.52*** (0.334)
    - (3) −0.689* (0.395)
- Policies and institutions (selected)
  - Unionization:
    - (1) −0.00635* (0.00363)
    - (2) −0.0226*** (0.00797)
    - (3) −0.00630 (0.00913)
    - (4) −0.00398 (0.00428)
    - (5) −0.00735 (0.00763)
    - (6) −0.0162* (0.00939)
  - Employment Protection Legislation:
    - (1) −0.00241 (0.00331)
    - (2) 0.00112 (0.00718)
    - (3) −0.00774 (0.00800)
  - Corporate Taxation:
    - (1) −1.28e-05 (0.000382)
    - (2) 5.86e-05 (0.000841)
    - (3) −0.000566 (0.000938)
- Fixed effects:
  - Sector Fixed Effects: Y in all columns shown

*Source: IMF staff calculations.*

### 0.0 percent in 2017 and 2018, respectively.

### text - 0.0 percent in 2017 and 2018, respectively.

### Euro irrevocable conversion rates (effective January 1, 1999)
- 1 euro = 13.7603 Austrian schillings
- 1 euro = 40.3399 Belgian francs
- 1 euro = 0.585274 Cyprus pound
- 1 euro = 1.95583 Deutsche marks
- 1 euro = 15.6466 Estonian krooni
- 1 euro = 5.94573 Finnish markkaa
- 1 euro = 6.55957 French francs
- 1 euro = 340.750 Greek drachmas
- 1 euro = 0.787564 Irish pound
- 1 euro = 1,936.27 Italian lire
- 1 euro = 0.702804 Latvian lat
- 1 euro = 3.45280 Lithuanian litas
- 1 euro = 40.3399 Luxembourg francs
- 1 euro = 0.42930 Maltese lira
- 1 euro = 2.20371 Netherlands guilders
- 1 euro = 200.482 Portuguese escudos
- 1 euro = 30.1260 Slovak koruna
- 1 euro = 239.640 Slovenian tolars
- 1 euro = 166.386 Spanish pesetas

Established dates noted in source:
- Turkmenistan conversion rate established on January 1, 2008.
- (2) Established on January 1, 2011.
- (3) Established on January 1, 2001.
- (4) Established on January 1, 2014.
- (5) Established on January 1, 2015.
- (6) Established on January 1, 2009.
- (7) Established on January 1, 2007.

### What’s New (selected items)
- On October 1, 2016, the Chinese renminbi joined the U.S. dollar, euro, yen, and British pound in the IMF’s SDR basket.
- Nauru added to the WEO database, expanding it to a total of 192 countries.
- Belarus redenominated its currency by replacing 10,000 old Belarusian rubles with 1 new Belarusian ruble; local currency data for Belarus are expressed in the new currency starting with the April 2017 WEO database.

### Data and conventions — scope, standards, and composite construction
- WEO database covers data and projections for 192 economies.
- Most countries’ macroeconomic data in the WEO conform broadly to the 1993 version of the System of National Accounts (SNA).
- IMF sector statistical standards referenced: BPM6, MFSM 2000, GFSM 2014; alignment with SNA 2008 is in progress; WEO estimates are only partially adapted to these manuals.
- Composite calculation rules:
  - Multiyear averages of growth rates are expressed as compound annual rates of change.
  - Arithmetically weighted averages are used for all data for the emerging market and developing economies group except inflation and money growth (geometric averages used for those).
  - Country group composites for exchange rates, interest rates, and growth rates of monetary aggregates are weighted by GDP converted to U.S. dollars at market exchange rates (averaged over the preceding three years) as a share of group GDP.
  - Composites for domestic-economy data (growth rates or ratios) are weighted by GDP valued at purchasing power parity as a share of total world or group GDP.
  - Euro area composites are corrected for reporting discrepancies in intra-area transactions; annual data are not adjusted for calendar-day effects; for data prior to 1999, aggregations apply 1995 European currency unit exchange rates.
  - Composites for fiscal data are sums of individual country data after conversion to U.S. dollars at the average market exchange rates in the years indicated.
  - Composite unemployment rates and employment growth are weighted by labor force as a share of group labor force.
  - External sector composites: sums of individual country data after conversion to U.S. dollars at the average market exchange rates in the years indicated for balance of payments data and at end-of-year market exchange rates for debt denominated in currencies other than U.S. dollars.
  - Composites of changes in foreign trade volumes and prices are arithmetic averages of percent changes for individual countries weighted by the U.S. dollar value of exports or imports as a share of total world or group exports or imports (in the preceding year).
  - Group composites are computed if 90 percent or more of the share of group weights is represented.
- Data refer to calendar years except for economies with exceptional reporting periods (see Table F).

### Country notes — key reporting exceptions and exclusions
- Argentina: CPI series changes across periods; average CPI inflation for 2014, 2015, and 2016 and end-of-period inflation for 2015 and 2016 are not reported in the April 2017 WEO. Labor market data publication discontinued in December 2015 and new series released starting Q2 2016.
- Argentina’s and Venezuela’s consumer prices are excluded from all WEO group aggregates.
- Greece: primary balance estimates for 2016 based on preliminary data as of February 15; accrual data (ESA 2010) to be available on April 21.
- Libya: data reliability low given civil war and weak capacities.
- Syria: data excluded from 2011 onward.
- Venezuela: projecting outlook complicated by lack of discussions with authorities, data gaps, and incomplete information; fiscal accounts for 2016–22 are IMF staff estimates and include budgetary central government and PDVSA; fiscal accounts before 2010 correspond to broader public sector coverage.

### Classification of countries in the WEO
- Two major groups: advanced economies and emerging market and developing economies.
- Advanced economies: 39 economies (Table B lists them).
- Emerging market and developing economies: 153 economies.
- Regional breakdowns for emerging market and developing economies: CIS, emerging and developing Asia, emerging and developing Europe, Latin America and the Caribbean (LAC), MENAP, and SSA.
- Analytical classifications:
  - By source of export earnings: fuel (SITC 3) and nonfuel; nonfuel primary products (SITCs 0, 1, 2, 4, and 68) highlighted.
  - By external financing source: net creditor economies, net debtor economies, heavily indebted poor countries (HIPCs), and low-income developing countries (LIDCs).
  - Net debtor definition: latest net international investment position < zero or current account accumulations from 1972 to 2015 negative.
  - HIPC group: countries considered by IMF and World Bank for the HIPC Initiative.
  - LIDCs: eligible for PRGT in 2013 review and as of 2011 had GNI per capita less than US$2,390 in 2011 Atlas method (and Zimbabwe).

### Selected aggregate shares and counts (from Table A)
- Advanced Economies: Number of economies = 39
  - Advanced Economies share of World GDP = 100.0 (group total shown as 100.0 for the group)
  - Advanced Economies share of World Exports of Goods and Services = 64.4 (group total)
  - Advanced Economies share of World Population = 14.5 (group total)
- Emerging Market and Developing Economies: Number of economies = 153
  - Emerging Market and Developing Economies share of World GDP = 100.0 (group total)
  - Emerging Market and Developing Economies share of World Exports of Goods and Services = 35.6 (group total)
  - Emerging Market and Developing Economies share of World Population = 85.5 (group total)
- Memorandum: Major Advanced Economies (G7) — Number of economies = 7; share of world GDP = 74.1; share of world exports = 53.9; share of world population = 10.4.

### Table and documentation highlights
- Table B: Advanced economies by subgroup (Major Currency Areas, Major Advanced Economies, Other Advanced Economies).
- Table C: European Union member list.
- Table D: Emerging market and developing economies by region and main source of export earnings (fuel vs. nonfuel primary products).
- Table E: Emerging market and developing economies by region, net external position, HIPC status, and LIDC status; dot (star) indicates net creditor (net debtor); dot instead of star indicates completion point for HIPC.
- Table F: Economies with exceptional reporting periods (national accounts and government finance reporting periods listed for specific economies).
- Table G: Key data documentation including currency, national accounts historical data source and latest actual annual data, System of National Accounts used, use of chain-weighted methodology, prices (CPI) historical data source and latest actual annual data, government finance historical data source and latest actual annual data, statistics manual in use at source, subsectors coverage, accounting practice, and balance of payments historical data source and latest actual annual data. (Numerous economy-specific entries listed.)

### Fiscal policy assumptions (summary of Box A1)
- Short-term fiscal policy assumptions normally based on officially announced budgets, adjusted for IMF staff macroeconomic assumptions and projected fiscal outturns.
- When no official budget exists, projections incorporate measures judged likely to be implemented.
- When insufficient information on authorities’ intentions, an unchanged structural primary balance is assumed unless indicated otherwise.
- Country-specific notes (selection):
  - Argentina: projections based on federal and provincial budget information, announced measures, and IMF staff macro projections.
  - Australia: projections based on Australian Bureau of Statistics data, fiscal year 2016/17 budget, 2016–17 Mid-year Economic and Fiscal Outlook, and IMF staff estimates.
  - Brazil: fiscal projections for end-2017 account for budget performance through December 31, 2016, and deficit target approved in budget law.
  - China: pace of fiscal consolidation likely more gradual reflecting reforms to strengthen social safety nets and social security system announced in Third Plenum reform agenda.
  - France: 2017 projections reflect the budget law; 2018–19 based on multiyear budget and April 2016 Stability Programme with IMF adjustments.
  - Japan: projections include announced fiscal measures, fiscal stimulus package for 2017, and the consumption tax hike in October 2019.
  - Puerto Rico: projections based on Puerto Rico Fiscal and Economic Growth Plan (FEGP); IMF assumes full implementation of FEGP measures; IMF projections on accrual basis differ from FEGP cash-basis projections.
  - Russia: 2016–19 projections based on authorities’ budget; 2020–22 projections based on proposed oil price rule assumed to be introduced in December 2017 with IMF adjustments.
  - Saudi Arabia: oil revenue projections based on WEO baseline oil prices; wage bill estimates from 2017 exclude the 13th-month pay previously awarded every three years.
  - United Kingdom: fiscal projections based on Budget 2017 (published March 2017) with IMF staff adjustments for macro assumptions; IMF staff data exclude public sector banks and effect of Royal Mail Pension Plan asset transfer.

*Source: World Economic Outlook — Statistical Appendix, April 2017 (International Monetary Fund).*

### 2012. Real government consumption and investment

### 2012. Real government consumption and investment

### Fiscal assumptions and projections (United States)
- Fiscal projections are based on the January 2017 Congressional Budget Office baseline adjusted for the IMF staff’s policy and macroeconomic assumptions.
- Baseline incorporates key provisions of the Bipartisan Budget Act of 2015, including a partial rollback of the sequester spending cuts in fiscal year 2016.
- For fiscal years 2017 through 2022, the IMF staff assumes sequester cuts will continue to be partially replaced, in proportions similar to fiscal years 2014 and 2015, with back-loaded measures generating savings in mandatory programs and additional revenues.
- Projections incorporate the Protecting Americans from Tax Hikes Act of 2015.
- Projections assume corporate and personal income tax cuts during 2017–19 cumulatively worth of about 1.8 percent of 2017’s GDP.
- Fiscal projections are adjusted to reflect IMF staff forecasts for macroeconomic and financial variables, different accounting treatment of financial sector support and defined-benefit pension plans, and are converted to a general government basis.
- Historical fiscal data start at 2001 for most series due to GFSM 2001 availability.

### Monetary policy assumptions (overview and country-specific)
- General framework: nonaccommodative stance over the business cycle — official rates rise when indicators suggest inflation will exceed acceptable rate/range; they fall when inflation is below acceptable rate/range and output growth is below potential with significant slack.
- Short-term rate assumptions (specific):
  - London interbank offered rate (LIBOR) on six-month U.S. dollar deposits: assumed to average 1.7 percent in 2017 and 2.8 percent in 2018.
  - Rate on three-month euro deposits: assumed to average –0.3 percent in 2017 and –0.2 percent in 2018.
  - Interest rate on six-month Japanese yen deposits: assumed to average 0.0 percent in 2017 and 2018.
- Country-specific monetary assumptions (selected):
  - Australia: in line with market expectations.
  - Brazil: consistent with gradual convergence of inflation toward the middle of the target range.
  - Canada: in line with market expectations.
  - China: monetary policy expected to tighten with a gradual rise in the interest rate.
  - Denmark: maintain the peg to the euro.
  - Euro area: in line with market expectations.
  - Hong Kong SAR: currency board system remains intact (assumed).
  - India: policy (interest) rate consistent with inflation within the Reserve Bank of India’s targeted band.
  - Indonesia: in line with maintenance of inflation within the central bank’s targeted band.
  - Japan: in line with market expectations.
  - Korea: in line with market expectations.
  - Mexico: consistent with attaining the inflation target.
  - Russia: assume increasing exchange rate flexibility as part of new inflation-targeting regime, with policy rates falling over the next year as inflation declines and second-round effects are subdued.
  - Saudi Arabia: projections based on continuation of the exchange rate peg to the U.S. dollar.
  - Singapore: broad money projected to grow in line with projected growth in nominal GDP.
  - Sweden: in line with Riksbank projections.
  - Switzerland: assume no change in the policy rate in 2016–17.
  - Turkey: broad money, long-term bond yield, and short-term deposit rate based on IMF staff projections.
  - United Kingdom: assume no change in the Bank Rate in the next two years, consistent with market expectations.
  - United States: following the Federal Reserve’s 25 basis point hike in mid-March, IMF staff expects the federal funds target rate to increase by 50 more basis points in 2017 and rise gradually thereafter.

### Major projections and growth figures (selected)
- Table A1: Summary of World Output (annual percent change, selected entries)
  - World: 2016 = 3.4; 2017 = 3.1; 2018 = 3.5; 2019–2022 median/projections include 3.6 and 3.8 in selected columns.
  - Advanced Economies: 2016 = 2.0; 2017 = 2.0; 2018 = 2.0.
  - United States: 2016 = 1.6; 2017 = 2.3; 2018 = 2.5.
  - Emerging Market and Developing Economies: 2016 = 4.2; 2017 = 4.1; 2018 = 4.5; 2022 = 5.0.
- Table A2: Advanced Economies: Real GDP (annual percent change, selected)
  - Advanced Economies (Real GDP): 2016 = 1.7; 2017 = 2.0; 2018 = 2.0.
  - United States (Real GDP): 2016 = 1.6; 2017 = 2.3; 2018 = 2.5.
  - Euro Area (Real GDP): 2016 = 1.7; 2017 = 1.7; 2018 = 1.6.
  - Japan (Real GDP): 2016 = 1.0; 2017 = 0.6; 2018 = 0.6.
- Table A3: Components of Real GDP (Advanced Economies, annual percent change, selected)
  - Private Consumer Expenditure (Advanced Economies): 2016 = 2.3; 2017 = 2.2; 2018 = 2.1.
  - Public Consumption (Advanced Economies): 2016 = 1.6; 2017 = 1.2; 2018 = 1.2.
  - Gross Fixed Capital Formation (Advanced Economies): 2016 = 1.5; 2017 = 2.8; 2018 = 3.5.
- Table A5: Summary of Inflation (GDP deflators and consumer prices, percent)
  - Advanced Economies GDP Deflators: 2016 = 1.2; 2017 = 1.0; 2018 = 1.6; 2019–22 = 1.7–1.9 in referenced columns.
  - Consumer Prices (Advanced Economies): 2016 = 0.3; 2017 = 0.8; 2018 = 2.0.
  - Emerging Market and Developing Economies (consumer prices): 2016 = 4.7; 2017 = 4.4; 2018 = 4.4; 2022 = 4.1.
- Table A8: Major Advanced Economies: General Government Fiscal Balances and Debt (percent of GDP, selected)
  - Major Advanced Economies Net Lending/Borrowing: 2016 = –3.5; 2017 = –3.3; 2018 = –3.3; 2022 = –3.5.
  - United States Net Lending/Borrowing: 2016 = –4.4; 2017 = –4.0; 2018 = –4.5; Net Debt: 2016 = 81.5; 2017 = 82.4; 2018 = 83.1.
  - Japan Gross Debt: 2016 = 239.2; 2017 = 239.2; 2018 = 239.4 (includes equity shares; nonconsolidated basis).
- Table A9: World trade (annual percent change, selected)
  - World trade volume: 2016 = 2.7; 2017 = 2.2; 2018 = 3.8; 2019–22 projections include 3.9.
  - Average oil price (U.S. dollars a barrel): 2016 average = 42.84; 2017 = 55.23; 2018 = 55.06.
- Table A10: Summary of Current Account Balances (billions of U.S. dollars, selected)
  - Advanced Economies current account (billions): 2016 = 224.2; 2017 = 232.6; 2018 = 296.6; 2022 = 374.6 (selected columns).
  - United States current account (billions): 2016 = –463.0; 2017 = –481.2; 2018 = –522.8; 2022 = –672.5.
  - Emerging Market and Developing Economies current account (billions): 2016 = 184.2; 2017 = 155.7; 2018 = –71.2; 2022 = –240.1.
- Table A13: Financial account balances (selected, billions of U.S. dollars)
  - Advanced Economies financial account balance: 2016 = 582.1; 2017 = 459.7; 2018 = 335.7; 2019 = 215.7 (selected).
  - United States financial account balance: 2016 = –195.2; 2017 = –406.5; 2018 = –522.9; 2019 = –672.6.
  - Emerging Market and Developing Economies financial account balance: 2016 = –16.6; 2017 = –283.4; 2018 = –347.1; 2019 = –49.7.

### Medium-term baseline highlights and projections (Table A15)
- World Real GDP: 2015 = 3.4; 2016 = 3.1; 2017 = 3.5; 2018 = 3.6; 2015–18 average = 3.4; 2019–22 projection = 3.7.
- Advanced Economies Real GDP: 2015 = 2.1; 2016 = 1.7; 2017 = 2.0; 2018 = 2.0; 2015–18 average = 2.0; 2019–22 = 1.7.
- Emerging Market and Developing Economies Real GDP: 2015 = 4.2; 2016 = 4.1; 2017 = 4.5; 2018 = 4.8; 2015–18 average = 4.4; 2019–22 = 5.0.
- World trade, volume (goods and services): 2016 = 2.2; 2017 = 3.8; 2018 = 3.9; 2015–18 average = 3.1; 2019–22 = 3.9.
- Consumer prices:
  - Advanced Economies: 2016 = 0.8; 2017 = 2.0; 2018 = 1.9; 2015–18 average = 1.2; 2019–22 = 2.0.
  - Emerging Market and Developing Economies: 2016 = 4.7; 2017 = 4.4; 2018 = 4.4; 2015–18 average = 4.5; 2019–22 = 4.5.
- Interest rates:
  - Real six-month LIBOR: 2015–18 average = –0.2; 2016 = –0.3; 2017 = –0.6; 2018 = 0.7.
  - World real long-term interest rate (GDP-weighted): 2015–18 average = 0.3; 2016 = –0.3; 2017 = 0.3; 2018 = 0.4.
- External metrics for Emerging Market and Developing Economies:
  - Total external debt: 2015 = 29.7; 2016 = 29.3; 2017 = 28.7; 2018 = 29.0; 2015–18 average = 28.7; 2019–22 = 27.4 (percent of GDP).
  - Debt service: 2015 = 10.5; 2016 = 10.0; 2017 = 9.8; 2018 = 10.6; 2015–18 average = 10.0; 2019–22 = 9.5 (percent).

*Source: IMF, World Economic Outlook: Gaining Momentum?, April 2017 (Statistical Appendix tables and Box A1 monetary/fiscal assumptions).*

### Appendix 2.1

### Appendix 2.1

### IMF Executive Board Discussion of the Outlook, April 2017
- Context and near-term outlook
  - Directors welcomed positive developments since the second half of 2016: global economic activity has accelerated, headline inflation has generally risen following a rebound in commodity prices, and financial market sentiment has strengthened.
  - Global growth is expected to pick up further in 2017–18, reflecting a stronger-than-expected recovery in many advanced economies and projected higher growth in many emerging market and developing economies, including from improved conditions in several commodity exporters.
  - Growth momentum is still modest and downside risks continue to dominate, with heightened policy uncertainty and persistent structural headwinds.

- Balance of risks and structural constraints
  - The balance of risks remain tilted to the downside, especially over the medium term.
  - In advanced economies: the ongoing cyclical recovery is encouraging, but output remains below potential and unemployment above precrisis levels in many countries. Population aging, low labor productivity growth, and crisis legacies are weighing on growth potential.
  - In emerging market and developing economies: medium-term prospects are closely linked to developments in commodity markets, global financial conditions, the ongoing economic transition in China, and progress in resolving domestic imbalances and structural challenges in some economies.
  - Elevated political and policy uncertainties cited include faster-than-expected normalization of interest rates; a rollback of financial regulation, which could spur excessive risk taking; and a potential rise in protectionist and inward-looking policies.

- Policy priorities and recommendations
  - Need for comprehensive, consistent, and well-communicated policy actions to achieve strong, sustainable, and balanced growth; enhance resilience; and ensure that the benefits of economic integration and technological progress are shared more widely.
  - Multilateral cooperation is essential to complement national efforts and to tackle common challenges, including:
    - preserving a rules-based, open trading system;
    - ensuring a level playing field in international taxation;
    - strengthening the global financial safety net;
    - addressing the withdrawal of correspondent banking relationships; and
    - addressing the refugee crisis.
  - Both deficit and surplus countries should implement appropriate policies to reduce persistent global excess imbalances.

- Boosting potential output in advanced economies
  - Fiscal and structural reforms should target country-specific priorities, including:
    - upgrade public infrastructure where needed;
    - improve labor force participation and skills;
    - eliminate product market distortions; and
    - reform corporate income taxation to promote private investment, research and development, and resource reallocation to productive areas.
  - Resisting a retreat from global economic integration to secure strong, sustainable global growth.

- Inclusion and adjustment to technological change and trade
  - Staff finding noted: technological progress appears to be the main factor explaining the decline in labor income share in advanced economies, while trade integration seems to be the dominant driver in emerging market economies.
  - Design of inclusive fiscal policies (transfer and tax instruments) should strike the right balance between promoting redistribution and maintaining incentives to invest and work.
  - Importance of improving education, training, health services, social insurance, and pension systems. In some cases, active labor market policies could be effective in the short term.

- Monetary and fiscal policy roles
  - Strengthening the recovery remains a priority, requiring support from both monetary and fiscal policies, combined with growth-enhancing structural reforms.
  - Where core inflation is persistently low and/or the risk of deflation remains tangible, unconventional monetary policies remain appropriate to support economic activity and lift inflation expectations, while their potential negative consequences on financial stability should be closely monitored.
  - Fiscal policy should be countercyclical, growth friendly, and promote inclusion, anchored in a credible medium-term framework that ensures debt sustainability.
  - Depending on country circumstances (economic slack, fiscal space, and debt levels), policy choices range from discretionary fiscal support to budget recomposition and rebuilding of fiscal buffers.

- Guidance for emerging market and developing economies
  - These economies can retain influence over domestic financial conditions but could face elevated risks from external negative spillovers, including a sudden reversal of market sentiment and sharp volatility in capital flows and exchange rates.
  - Critical measures include:
    - maintaining sound policies and strong frameworks, including exchange rate flexibility and a robust macroprudential toolkit;
    - using capital flow management measures temporarily as warranted, though not as a substitute for warranted macroeconomic adjustment;
    - proactively monitoring vulnerabilities and addressing weaknesses in the corporate and banking sectors;
    - improving corporate governance; and
    - reducing infrastructure bottlenecks and barriers to entry.
  - Complementary resilience measures: developing a local investor base, fostering depth and liquidity in the equity and bond markets, and upgrading the tax system to promote efficient use of resources.

- Financial stability and regulatory policy
  - Solidifying improvements in financial stability and market expectations requires concerted efforts across countries.
  - United States: authorities should be vigilant to increases in leverage and deterioration in credit quality amid tax reform and financial deregulation, and should take preemptive measures against excessive risk taking.
  - Europe: further efforts needed to adjust bank business models, facilitate the disposal of nonperforming loans, and remove structural impediments to bank profitability.
  - China: pay attention to rapid growth in assets among smaller banks, increasing reliance on wholesale funding, and close interconnections between shadow products and interbank markets.
  - At the global level: completing the regulatory reform agenda remains important, and a rollback of regulatory standards should be resisted.

- Commodity-exporting low-income developing countries
  - These countries have faced a difficult adjustment process since the commodity cycle turned in 2014.
  - In light of rising debt and weaker external positions in several of these economies, Directors called for intensified policy efforts to:
    - mobilize revenue;
    - improve tax administration;
    - enhance spending efficiency; and
    - contain the buildup of debt.
  - For many diversified countries, priorities are to build fiscal buffers while growth remains relatively strong and to achieve a better balance between meeting social and developmental needs and securing debt sustainability.
  - A common challenge across all low-income developing countries is to maintain progress toward attaining their sustainable development goals.

*IMF Executive Board discussion remarks as presented at the conclusion of the Executive Board’s discussion of the Fiscal Monitor, Global Financial Stability Report, and World Economic Outlook on April 4, 2017.*

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_Source: https://www.imf.org/-/media/files/publications/weo/2017/april/pdf/text.pdf_