## areo0517

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### Recent developments and near-term outlook
- Asia-Pacific outlook: "robust—the strongest in the world" with pickup in momentum.
- Growth forecasts and projections:
  - Growth is forecast to accelerate to 5.5 percent in 2017 from 5.3 percent in 2016.
  - Growth is projected at 5.4 percent in 2018.
  - World economic growth: 3.1 percent in 2016 → 3.5 percent in 2017 → 3.6 percent in 2018.
  - China: growth was 6.7 percent in 2016; GDP growth projected at 6.6 percent in 2017 and 6.2 percent in 2018.
  - Japan: growth in 2016 was 1 percent; growth projected at 1.2 percent in 2017.
  - India: growth for FY2016–17 expected to decelerate to 6.8 percent; projected to rebound to 7.2 percent in FY2017–18 and to 7.7 percent in FY2018–19.
  - Korea: growth was 2.8 percent in 2016; expected 2.7 percent in 2017 and 2.8 percent in 2018.
  - Asia aggregate GDP growth forecasts: 2017: 5.5 percent; 2018: 5.4 percent.
- Financial and market developments:
  - Net portfolio inflows to major Asian emerging market economies (excluding China): $51 billion in 2016 (up from $42 billion in 2015; pre-U.S. elections peak $72 billion).
  - China capital outflows estimated at $320 billion in 2016; January–February 2017 outflows $26 billion.
  - China’s foreign exchange reserves fell below $3 trillion temporarily in January 2017 (about $1 trillion decline from peak near $4 trillion in mid-2014).
  - Stock and bond markets: Asian stock markets rose significantly to mid-March 2017; sovereign bond yields increased since mid-2016.
- Inflation and external balances:
  - Asia’s current account surplus: estimated 2.5 percent of GDP for 2016 (from 2.7 percent in 2015).
  - Headline inflation projected to rise to 2.9 percent in 2017 and 2018 for the region.

### Risks to the outlook
- Near-term upside risks:
  - Additional stimulus in the United States and stronger growth in China could provide short-run support.
- Near-term downside risks:
  - Tighter global financial conditions triggering capital flow volatility interacting with balance sheet weaknesses.
  - More inward-looking policies in advanced economies given the region’s trade openness.
  - A bumpier-than-expected transition in China with large spillovers.
  - Geopolitical tensions and domestic political uncertainties.
- Medium-term secular headwinds:
  - Population aging in some countries.
  - Slowing productivity catch-up.

### Regional financial resilience and vulnerabilities
- Credit, debt, and leverage:
  - Credit growth (adjusted for inflation) in 2016 remained robust but below previous-decade average in most economies; exceptions: Hong Kong SAR, New Zealand, Philippines.
  - In China, credit growth continues at twice the pace of nominal GDP; stock of total social financing grew at 16 percent in 2016 (adjusted for local government bond swaps).
  - Private debt and corporate debt are high across the region, notably in China and India.
  - Household-debt-to-GDP ratio (2015): range from 10 percent in India to 124 percent in Australia; increased by more than 20 percentage points between 2007 and 2015 in China, Malaysia, and Thailand.
- Financial-stability indicators:
  - House prices above long-term averages in Australia, China, Hong Kong SAR, Malaysia, New Zealand, and Thailand.
  - Benchmark equity indices above long-term averages in Australia, India, Indonesia, and the Philippines.
  - Tier 1 capital ratios increased in most economies (notably Hong Kong SAR, Indonesia, Thailand) but declined in the Philippines.
  - Nonperforming loan ratios remain relatively low across most economies but are relatively high in India; banks’ profitability has generally declined.

### Demographics — "growing old before becoming rich"
- Main concern: parts of Asia risk "growing old before becoming rich."
- Speed of aging:
  - Many Asian countries experience faster aging than historical European and U.S. experience; several transitions (old-age dependency ratio 15→20 percent) occur in less than 10 years in China, Japan, Korea, Thailand, Singapore, Vietnam.
- Population and dependency projections (selected series and figures from Table 2.2):
  - Japan old-age dependency ratio: 43.3 in 2015; projected 71.0 by 2050.
  - Hong Kong SAR old-age dependency series (2000–2050): 15.3, 16.5, 17.2, 20.6, 26.5, 35.1, 43.7, 50.1, 55.6, 60.4, 64.6.
  - Korea old-age dependency series (2000–2050): 10.2, 12.7, 15.0, 18.0, 22.2, 29.4, 37.6, 46.1, 54.4, 60.7, 65.8.
  - China old-age dependency series (2000–2050): 9.7, 10.4, 11.1, 13.1, 17.1, 20.4, 25.3, 32.7, 39.6, 43.0, 46.7.
- Growth implications (average 2020–50, impact on real GDP growth):
  - Japan: impact could reduce average annual growth by almost 1 percentage point.
  - China, Hong Kong SAR, Korea, Thailand: impact between one-half and three-quarters of a percentage point.
  - Philippines: close to 1½ percent per year demographic dividend.
  - New Zealand: about ½ percent per year demographic dividend.
- Labor force participation scenarios:
  - A gradual increase in LFPRs for all age and gender groups by 6 percentage points (Japan’s experience 1990–2015) could boost annual GDP growth by 0.2 to 0.3 of a percentage point.
  - Eliminating the employment gender gap could add ¼ of a percentage point to annual GDP growth for Japan and up to 1 percentage point for India by 2050 (citing various studies).

### Demographics — impacts on TFP, interest rates, and external balances
- Aging and TFP:
  - For pooled Asian and European sample: a 1 percentage point increase in the 55–64 age cohort associated with reduction in TFP; Annex result: a 1 percentage point increase in the 55–64 cohort associated with a reduction in total factor productivity of 0.74 of a percentage point (Annex Table 2.1.1).
  - Workforce aging associated with lower annual TFP growth by 0.1 to 0.3 of a percentage point on average for Asia; figure-based estimate: average older workforce reduces growth by 0.2 percent per year; China biggest impact at 0.3 percent per year.
- Interest rates and assets:
  - Demographic trends could put downward pressure on interest rates by about 1 to 2 percentage points in the next decade, all else equal.
  - Key regression coefficients (Annex Table 2.1.3) for 10-year real interest rate:
    - Youth dependency Ratio: 9.41*** (2.46)
    - Old-age dependency Ratio: −18.3*** (6.28)
    - Aging speed: −29.7*** (11.06)
    - World Interest Rate: 0.65*** (0.16)
  - Openness mitigates domestic demographic impacts on interest rates (interaction results; Annex Table 2.1.5).
- External balance (EBA model):
  - Demographic variables used: population growth, old-age dependency ratio, aging speed.
  - Over 2020–30, demographics likely to exert upward pressure on current account balances in surplus countries (Japan, Korea, Thailand) and downward pressure in deficit countries (particularly New Zealand); changes in population growth have small contributions (less than 0.1 percent of GDP).

### Fiscal and welfare implications of aging
- Projected increases in age-related public expenditures (pensions and health care) under current policies: up to 10 percentage points of GDP by 2050 in some countries.
- Public pensions:
  - Projected increases more than 5 percentage points of GDP by 2050 in China, Korea, New Zealand, Thailand, and Vietnam absent policy measures.
  - Early-dividend countries (India, Indonesia, Philippines): pension expenditures broadly unchanged as percent of GDP.
- Health care:
  - Projected increases >3 percentage points of GDP by 2050 in post-dividend countries with generous systems (Korea and Japan) absent reforms.
  - Japan health care reform could yield fiscal savings of 2 percent of GDP by 2030 (Nozaki, Kashiwase, and Saito 2014).

### Productivity: the "new mediocre" and policy priorities
- Productivity slowdown since the global financial crisis:
  - Slowdown most severe in advanced economies of the region and in China.
  - Contributing factors: sluggish investment, limited impetus from trade, slowing human capital formation, reallocation to less productive sectors, and aging.
- Empirical findings on drivers:
  - R&D, imports, and inward FDI positively associated with labor productivity growth in sector-level regressions; imports of intermediate inputs an important channel.
  - Panel results (Annex Table 3.2.2, Asia-Pacific group): R&D Stock: 0.005*** (0.001); FDI Stock: 0.089*** (0.007); Imports: 20.001*** (0.000).
  - Absorptive capacity matters: Interaction of FDI Stock and Human Capital positive and significant in several specifications (Annex Table 3.2.3).
- Sectoral patterns:
  - Manufacturing historically accounted for about half of aggregate labor productivity growth but has slowed, notably in China.
  - Services productivity growth is substantially lower than manufacturing; raising services productivity is a priority.
- Policy priorities by country group:
  - Advanced economies: strengthen effectiveness of R&D spending; raise productivity in services; support trade integration and liberalization in services.
  - Emerging market and developing economies: increase absorptive capacity and domestic investment to capitalize on increased FDI inflows.
  - Cross-cutting: promote trade liberalization, infrastructure, human capital, and market-oriented reforms to raise TFP.

### Key country near-term projections and country highlights (selected)
- China: GDP growth projected at 6.6 percent in 2017 and 6.2 percent in 2018; vulnerabilities from continued rapid credit growth and high leverage; moderation assumes housing cooling and stable augmented fiscal deficit.
- Japan: 2017 growth projected at 1.2 percent; fiscal stimulus and postponement of VAT hike contributed to 2016–17 stance; net exports contribution expected to narrow in 2018.
- India: projected rebound to 7.2 percent in FY2017–18 and 7.7 percent in FY2018–19; IMF staff estimates cash shortages likely to slow FY2016/17 growth by about 4/5 of 1 percentage point and FY2017/18 growth by about ½ of 1 percentage point (Box 1.1).
- ASEAN economies (selected projections):
  - Indonesia: 5.1 percent in 2017 and 5.3 percent in 2018.
  - Malaysia: 4.5 percent in 2017 and 4.7 percent in 2018.
  - Thailand: 3 percent in 2017 and 3.3 percent in 2018.
  - Philippines: 6.8 percent in 2017 and 6.9 percent in 2018.
  - Singapore: 2.2 percent in 2017 and 2.6 percent in 2018.
  - Vietnam: 6.5 percent in 2017 and 6.3 percent in 2018.

### Country case: India’s November 8, 2016 currency withdrawal (Box 1.1) — impacts and staff estimates
- Action: legal tender status withdrawn for existing 500 and 1,000 rupee banknotes; notes affected about 15 trillion rupees (about 86 percent of cash in circulation).
- Cash economy indicators:
  - Currency in circulation in India ≈ 12 percent of GDP at end-2015.
  - Cash accounted for about three-quarters of the narrow money base.
- Near-term economic impacts:
  - Purchasing Manager’s Index for services fell from 55 in October 2016 to 43 in November 2016.
  - Growth of credit to nonfood private sector decelerated from 9 percent at end-October 2016 to 4 percent by end-December 2016.
  - Consumer goods component of industrial production declined about 7 percent in December 2016; consumer durables production fell by 10 percent.
  - Domestic motor vehicle sales declined 20 percent in December 2016 vs December 2015.
  - Remonetization: about 75 percent of predemonetization level of currency in circulation restored by late March (2017).
- IMF staff modeled cash shortages as a temporary tightening of monetary conditions: GDP growth slowed in second half of FY2016/17, with rebound in FY2017/18; quantified slowing of growth by about 4/5 of 1 percentage point in FY2016/17 and about ½ of 1 percentage point in FY2017/18.

### Policy recommendations — macro and structural (summarized)
- Monetary policy:
  - Generally remain accommodative given inflation below target and slack in most economies.
  - Some central banks should stand ready to raise policy rates if inflationary pressures gather (examples: India, Indonesia, Vietnam).
  - Some central banks may have room to lower rates if growth slides and external stability not compromised (examples: Malaysia, Thailand).
- Macroprudential policy:
  - Tighten settings in some countries to slow credit growth.
  - Rely on macroprudential policies to mitigate systemic risks from high corporate and household leverage and rising interest rates; use to increase resilience to shocks including capital-flow reversals.
- Fiscal policy:
  - Support and complement structural reforms and external rebalancing where fiscal space exists.
  - Countries with closed output gaps should start rebuilding fiscal space; deliver on medium-term consolidation where debt levels are high.
  - Reorient spending composition to allow infrastructure and social spending while securing debt sustainability.
- Exchange rate and external adjustment:
  - Exchange rate flexibility should generally remain the main shock absorber against sudden tightening in global financial conditions or protectionism.
  - Judicious foreign exchange intervention may be used to prevent disorderly market conditions if sufficient reserve buffers exist, but not to resist movements reflecting fundamentals.
- Structural reforms to sustain long-term growth:
  - Address demographic transition: pension reform, raise labor force participation (women, elderly), guest worker programs, active labor market policies.
  - Boost productivity: enhance openness, FDI, absorptive capacity, domestic investment, R&D effectiveness, and services productivity.
  - Strengthen measures to reduce external imbalances and mitigate vulnerabilities.
- Country-specific mix:
  - Appropriate policy mix varies across economies depending on output gaps, policy space, reform priorities, and need for external rebalancing.

_International Monetary Fund | April 2017_

### Executive	Summary	xiii

### Executive Summary

### Recent developments and near-term outlook
- The outlook for the Asia-Pacific region remains robust—the strongest in the world—and recent data point to a pickup in momentum.
- Growth is forecast to accelerate to 5.5 percent in 2017 from 5.3 percent in 2016.
- Growth is projected at 5.4 percent in 2018.
- World economic growth is forecast to accelerate from 3.1 percent in 2016 to 3.5 percent in 2017 and 3.6 percent in 2018.
- Growth in China and Japan is revised upward for 2017 compared to the October 2016 World Economic Outlook, owing mainly to continued policy support and strong recent data.
- Growth is revised downward in India due to temporary effects from the currency exchange initiative and in Korea owing to political uncertainty.
- Over the medium term, slower growth in China is expected to be partially offset by an acceleration of growth in India, underpinned by key structural reforms.
- Forward-looking indicators such as the Purchasing Managers’ Index suggest continued strength in activity into early 2017.
- Despite volatile capital flows, Asian financial markets have been resilient, reflecting strong fundamentals.
- The near-term outlook is clouded with significant uncertainty, and risks, on balance, remain slanted to the downside.

### Risks to the outlook
- Near-term upside risks:
  - Additional stimulus in the United States and stronger growth in China could provide short-run support.
- Near-term downside risks:
  - Tighter global financial conditions could trigger capital flow volatility, interacting with balance sheet weaknesses in a number of economies.
  - More inward-looking policies in advanced economies would significantly impact Asia, given the region’s trade openness.
  - A bumpier-than-expected transition in China would have large spillovers.
  - Geopolitical tensions and domestic political uncertainties could burden specific countries’ outlooks.
- Medium-term secular headwinds:
  - Population aging in some countries.
  - Slowing productivity catch-up.

### Chapter highlights: demographics (Chapter 2)
- Main concern: parts of Asia risk “growing old before becoming rich.”
- Speed of aging is especially notable compared to the experience in Europe and the United States.
- For many countries, on current trends, per capita income (benchmarked against the United States) will be much lower than that reached by advanced economies at a similar peak in their aging cycle.
- The drag on future growth from aging could be significant especially in relatively old Asian countries.
- Policy implications emphasized: protecting vulnerable elderly, raising labor force participation (especially for women and the elderly), pension reform, and early macroeconomic policy adjustments to safeguard debt sustainability.

### Chapter highlights: productivity (Chapter 3)
- Productivity growth has slowed since the global financial crisis, with limited catch-up (“convergence”) toward the United States and other countries at the technological frontier.
- The slowdown has been most severe in the advanced economies of the region and in China.
- Contributing factors include sluggish investment, limited impetus from trade, slowing human capital formation, reallocation of resources to less productive sectors, and the aging population.
- Without reforms, productivity growth will likely remain low for some time, with headwinds from rapid aging becoming increasingly important.
- Empirical results stress the importance of openness and foreign direct investment (FDI) in boosting productivity, particularly for emerging market and developing economies.
- Advanced economies should strengthen the effectiveness of R&D spending, raise productivity in services sectors, and support trade integration and liberalization in services.
- Emerging market and developing economies should increase absorptive capacity and domestic investment to capitalize on increased FDI inflows.

### Policy recommendations
- Monetary policy:
  - Should generally remain accommodative, given that inflation is below target and there is slack in most economies in the region.
  - Some central banks should stand ready to raise the policy rate if inflationary pressures gather pace.
- Macroprudential policy:
  - Tighten settings in some countries to slow credit growth.
  - Rely on macroprudential policies to mitigate systemic risks associated with high corporate and household leverage and rising interest rates.
  - Use macroprudential tools to increase resilience to shocks, including shocks associated with reversal of capital flows.
- Fiscal policy:
  - Should support and complement structural reforms and external rebalancing, where needed and fiscal space is available.
  - Countries with closed output gaps should start rebuilding fiscal space.
  - Delivering on medium-term fiscal consolidation plans is critical in some countries, especially where debt levels are high and fiscal credibility needs to be enhanced.
- Exchange rate and external adjustment:
  - Exchange rate flexibility should generally remain the main shock absorber against a sudden tightening in global financial conditions or a shift toward protectionism in major trading partners.
- Structural reforms to sustain long-term growth:
  - Address demographic transition through pension reform and policies to raise labor force participation.
  - Boost productivity via policies that enhance openness, FDI, absorptive capacity, domestic investment, R&D effectiveness, and productivity in services.
  - Strengthen measures to reduce external imbalances, mitigate domestic and external vulnerabilities, and promote faster and more inclusive growth.
- Country-specific mix:
  - The appropriate policy mix varies across economies, depending on the output gap, policy space, reform priorities, and the need for external rebalancing.

*International Monetary Fund | April 2017*

### 1.  Preparing for Choppy Seas

### 1.  Preparing for Choppy Seas

### Global outlook and risks
- The April 2017 World Economic Outlook envisages a faster rebound in activity in advanced economies and marginally weaker growth in emerging market and developing economies.
- Headline inflation has increased in advanced economies, but core inflation remains subdued and heterogeneous.
- In emerging market economies, the revival in headline inflation is more nascent; core inflation is generally muted and broadly stable in most emerging market economies.
- For 2017 and 2018, with the uptick in commodity prices, a broad-based increase in headline inflation rates is projected in advanced, emerging market, and developing economies.
- Global financial conditions have started to tighten but remain accommodative on balance with favorable market sentiment.
- Expectations of looser fiscal policy and tighter monetary policy in the United States have contributed to a stronger dollar and higher U.S. Treasury interest rates, pushing up yields elsewhere.
- Risks are tilted to the downside amid broad policy uncertainty, including:
  - A possible sharp increase in risk aversion.
  - Wide range of upside and downside risks from U.S. policy actions to the U.S. and global baseline forecasts.
  - Adverse feedback loops between weak demand and balance sheet problems in parts of Europe.
  - Disruption of global trade, capital, and labor flows from inward shifts in policies in some advanced economies, with potential to disrupt global value chains, deter investment, reduce productivity, and lower global growth.
  - Tightening of economic and financial conditions in emerging market economies, given balance sheet weaknesses in some economies and building vulnerabilities in China’s financial system, with potentially large spillovers.
  - Noneconomic factors: geopolitical tensions, domestic political discord, terrorism and security concerns.

### Regional financial developments: resilience amid volatile capital flows
- Net portfolio inflows to major Asian emerging market economies (excluding China) reached $51 billion in 2016, up from $42 billion in 2015 but below the peak of $72 billion prior to the U.S. elections.
- In China, capital outflows accelerated since September 2016, with total outflows reaching an estimated $320 billion in 2016, driven by residents’ asset purchases abroad.
- China’s capital outflow pressure subsided in early 2017, amounting to $26 billion during January–February 2017, with tightening of capital controls and resumed portfolio inflows.
- Asian stock markets rose significantly in the year prior to mid-March 2017; sovereign bond yields have increased since mid-2016 following the rise in yields in advanced economies.
- The increase in yields accelerated following the U.S. elections—one exception is India, where yields declined owing to the currency exchange initiative.
- Sovereign credit default swap (CDS) spreads have increased in some emerging market economies but are generally below their levels on the eve of the “taper tantrum” episode in May 2013.
- Demand for frontier and developing Asia’s debt remains strong (example: Mongolia’s recent bond issue heavily over-subscribed).
- In some economies (Australia, Japan, Korea), CDS spreads are at or close to the lowest levels reached during the past four years.
- Exchange rates have generally depreciated over the past year and a half, reflecting a stronger U.S. dollar.
  - After the U.S. elections, exchange rates depreciated across most of the region by an average of 2 percent.
  - The yen depreciated against the dollar by 8 percent.
  - The renminbi weakened against the U.S. dollar by less than most emerging market currencies and was broadly stable in effective terms.
- Foreign exchange reserves were broadly stable for most countries, but China’s foreign exchange reserve losses picked up.
  - China’s reserves fell below $3 trillion temporarily in January 2017 for the first time since 2011, with an overall decline of about $1 trillion from their peak of nearly $4 trillion in mid-2014.
- Financial conditions in the region are still accommodative but have begun to tighten in some countries.
- Credit growth (adjusted for inflation) in 2016 remained robust in the region but was well below the average of the previous decade in most economies, with exceptions: Hong Kong SAR, New Zealand, and the Philippines.
- In China, credit growth continues at twice the pace of nominal GDP; the stock of total social financing (adjusted for local government bond swaps) grew at 16 percent in 2016.
- Foreign bank lending to Asia has risen; corporate debt issuance (including syndicated loans) is in general lower.
- Private debt levels remain high across most of the region, with corporate debt levels in Asia higher than in other regions, particularly in China and India.
- Household debt increased considerably between 2007 and 2015; the household-debt-to-GDP ratio increased by more than 20 percentage points in China, Malaysia, and Thailand.
- Evidence suggests excessive credit growth is decelerating in many major economies, with the credit-to-GDP gap declining in Hong Kong SAR, Indonesia, Malaysia, Singapore, and Thailand, but remaining substantial in several economies and still increasing in China.
- A large credit gap has been found to provide an early warning signal of increasing vulnerabilities for advanced and emerging market economies.

### Financial stability and banking sector indicators
- Financial stability heat map highlights risks associated with house prices and equity market overvaluation in some economies.
  - House prices are above long-term averages in Australia, China, Hong Kong SAR, Malaysia, New Zealand, and Thailand.
  - Benchmark equity indices are above long-term averages in Australia, India, Indonesia, and the Philippines.
- Banking sector capitalization has improved overall in recent years; liquidity has been stable; asset quality and profitability have deteriorated in a number of Asian economies.
- Tier 1 capital ratios increased in most economies—particularly Hong Kong SAR, Indonesia, and Thailand—but declined in the Philippines.
- Bank liquidity, measured by loan-to-deposit ratios, was stable in major economies.
- Nonperforming loan ratios remain relatively low across most economies but have increased recently in several countries and are relatively high in India.
- Banks’ profitability has generally declined.

### Regional activity: recovery since mid-2016 with positive momentum
- Asia’s growth declined to 5.3 percent in 2016 from 5.6 percent in 2015.
- Net exports subtracted 0.1 of a percentage point from regional growth in 2016.
- Asia’s export growth momentum (in values) recovered in the second half of 2016, particularly to China and Japan and, to some extent, the United States; exports to the euro area also recovered but remain declining year over year.
- Export volumes increased less than nominal values (partly reflecting higher commodity prices) but have started to show some improvement.
- Factors driving the export recovery include strong growth in China and the recovery in advanced economies; there is some evidence that inventory destocking, particularly in electronics, may have ended, as Asian exports now more closely follow demand in advanced economies.
- Domestic demand remained strong, supported by robust private consumption owing to continued growth in household income; retail sales were relatively solid overall.
  - High-frequency indicators suggest retail sales declined sharply in India due to the currency exchange initiative.
  - In Hong Kong SAR, retail sales remain depressed owing to a downturn in tourism arrivals from mainland China.

*Source: IMF, Regional Economic Outlook: Asia and Pacific, April 2017.*

### 1.  PREPARING fOR ChOPPy sEAs

### 1.  PREPARING fOR ChOPPy sEAs

### Inflation and commodity prices
- The recovery in commodity prices has modestly pushed up headline inflation in many Asian economies, while core inflation generally remains stable at low levels.
- Commodity price levels are still comparatively low—barely reaching their mid-2015 levels.
- In China, producer price inflation turned significantly positive and consumer price inflation picked up.
- Headline inflation in Japan fell during most of 2016, while core inflation remained negative but edged up closer to zero.
- Headline inflation exceeded 3 percent in 2016 only in a few economies.
- Inflation expectations (from Consensus Forecasts) remain weak in most economies and have declined recently, although a few economies (for example, China and the Philippines) saw a slight uptick.
- Core inflation has been low across most of Asia but has increased in several countries, including China, the Philippines, New Zealand, Singapore, and Vietnam.

### Current account balances
- Asia’s current account surplus declined to an estimated 2.5 percent of GDP for 2016, down from 2.7 percent in 2015.
- Industrial Asia: Current account balances increased by 1.2 percentage points in 2016 to 2.4 percent of GDP.
  - Japan: current account rose to 3.9 percent of GDP due to a stronger goods trade balance.
  - Australia and New Zealand: current account deficits narrowed, reflecting higher prices of commodity exports.
- East Asia and ASEAN: reduced current account surpluses in aggregate in 2016.
  - China: current account surplus narrowed to 1.8 percent of GDP from 2.7 percent in 2015, driven by a lower trade surplus and an increase in the services deficit.
  - Korea: current account surplus narrowed to 7 percent, owing to lower exports due to temporary disruptions in automobile and smartphone production, and the bankruptcy of a major shipping company.
  - Malaysia: current account balance declined to 2 percent of GDP mainly on weaker oil and gas trade balances.
  - Philippines: current account surplus fell to 0.2 percent of GDP due to strong growth in imports, particularly capital goods.
  - Thailand: current account surplus increased to 11.4 percent of GDP due to buoyant tourism and weak imports as domestic demand slowed.

### GDP growth trends and country heterogeneity (2016 outcomes)
- China: growth was 6.7 percent in 2016, slightly higher than projected in the October 2016 World Economic Outlook, reflecting a rebounding housing market, robust consumption growth, and continued policy support; net exports continued to be a drag.
- Japan: growth in 2016 was 1 percent after upward revisions to 2013–15 national accounts; strong net exports were the most significant role in 2016.
- India: Growth for FY2016–17 is expected to decelerate to 6.8 percent, 0.8 of a percentage point lower than the projection in the October 2016 World Economic Outlook; post-November 8, 2016, cash shortages and payment disruptions from the currency exchange initiative strained consumption and business activity.
- Korea: growth was 2.8 percent in 2016, mainly driven by stronger construction investment while private consumption was weaker than expected.
- Hong Kong SAR: growth slowed to 1.9 percent in 2016 due to an anemic global trade environment and a sharp downturn in tourism arrivals from mainland China, with signs of recovery in the second half from strong public investment.
- Australia: growth was 2.5 percent in 2016, reflecting a drag from mining investment and slightly weaker consumption.
- New Zealand: growth accelerated to 4 percent, driven mainly by construction activity following the 2011 Canterbury earthquake; more recently expansion has been broad based.
- ASEAN economies (2016):
  - Indonesia: growth accelerated to 5 percent, supported by robust private consumption.
  - Malaysia: growth at 4.2 percent—the slowest rate since the global financial crisis—driven mainly by private domestic demand; net exports contributed negatively.
  - Thailand: growth reached 3.2 percent, primarily driven by services (notably tourism) and public investment.
  - Philippines: growth increased to 6.8 percent, driven by domestic demand—investment growth strong due to higher public infrastructure spending and private construction.
  - Singapore: growth was 2 percent, reflecting population aging, tighter limits on immigration, the turning of the financial cycle, and external headwinds.
  - Vietnam: growth slowed to 6.2 percent, reflecting a severe drought and a sharp contraction in oil production.
- Frontier economies and small states: on average, growth slowed in 2016 with considerable variation.
  - Lao P.D.R.: growth declined to 6.9 percent owing to slowing trading partners, lower metals prices, and poor agricultural weather.
  - Mongolia: growth slowed sharply as uncertainties sapped private sector confidence.
  - Nepal: growth decelerated sharply to 0.6 percent due to the 2015 earthquakes and border blockade disruptions.
  - Sri Lanka: growth decelerated to 4.3 percent due to a contraction in agriculture from floods and drought.
  - Bangladesh: growth reached 6.9 percent, largely driven by private consumption.
  - Bhutan: growth recovered to 6.2 percent, driven by services, mining, and hydropower-related construction.
  - Maldives: growth recovered to 3.9 percent following reduced policy uncertainty and political tension.
  - Cambodia: growth remained strong at 7 percent, driven by garment exports, real estate, and construction.
- Pacific island countries: growth dampened overall due to lower commodity prices; Papua New Guinea decelerated owing to low commodity prices and a major drought; Fiji disrupted by Cyclone Winston. Tourism-linked countries (Fiji and Vanuatu) benefited from a stronger U.S. dollar and rapid growth of Chinese tourism; Palau saw less benefit due to base effects.

### Near-term regional outlook and projections
- Asia aggregate GDP growth forecasts:
  - 2017: 5.5 percent.
  - 2018: 5.4 percent.
- Growth in 2017 was revised up by 0.1 of a percentage point compared to the October 2016 World Economic Outlook.
- Accommodative policies will underpin domestic demand, offsetting tighter global financial conditions.
- The aggregate outlook masks significant country-level revisions:
  - China and Japan: 2017 projections revised upward owing to policy support and strong late-2016 data; part of Japan’s upward revision due to national accounts revision.
  - India and Korea: 2017 projections revised downward (India due to currency exchange initiative; Korea due to political uncertainty).
  - Asia excluding India and Korea: 2017 projected growth revised upward by 0.3 of a percentage point compared to the October 2016 World Economic Outlook.
- Asian trade expected to recover; net exports projected to be less of a drag for most economies due to improved global growth outlook and higher commodity prices.
- Domestic demand expected to remain resilient, supported by robust labor markets, healthy disposable income growth, and policy support; low inflation is boosting real incomes in most economies.
- High-frequency indicators and purchasing manager indices suggest continued strength into early 2017; the IMF Asia and Pacific Department’s indicator model points to strong growth momentum with projections slightly higher than World Economic Outlook projections.
- Credit gaps have started to decline in several major economies, though credit growth is expected to remain mildly supportive of domestic demand in the near term.

### Country-specific near-term projections and risks
- China:
  - GDP growth projected at 6.6 percent in 2017 and 6.2 percent in 2018.
  - Near-term outlook revised up due to policy support (especially rebound in real estate); inflationary pressure is picking up.
  - Continued rapid credit growth exacerbates already-high vulnerabilities.
  - Moderation assumes cooling housing market from tightening measures, consumption moderating with weaker wage growth, and a stable augmented fiscal deficit (including contingent liabilities from off-budget local government borrowing).
- Japan:
  - Growth projected at 1.2 percent in 2017.
  - Net exports contribution expected to narrow as imports recover and exports are boosted by foreign demand.
  - Fiscal stimulus and postponement of the VAT hike (from April 2017 to October 2019) generated a slightly expansionary 2016–17 fiscal stance; the dissipation of this impact in 2018 is expected to reduce growth despite anticipated private investment related to the 2020 Tokyo Olympics.
- India:
  - Growth projected to rebound to 7.2 percent in FY2017–18 and to 7.7 percent in FY2018–19.
  - Temporary disruptions from cash shortages accompanying the currency exchange initiative expected to dissipate in 2017.
  - Tailwinds from a favorable monsoon and progress in resolving supply-side bottlenecks expected to support activity.
  - Investment recovery expected to remain modest and uneven as deleveraging occurs; bank and corporate balance sheet weaknesses will weigh on near-term credit growth.
  - Continued fiscal consolidation and anti-inflationary monetary policy support macroeconomic stability.
- Korea:
  - Growth expected at 2.7 percent in 2017 and 2.8 percent in 2018.
  - Lower consumption will weigh on growth, reflecting heightened uncertainty amid political turmoil.
- Australia:
  - Growth expected to reach 3.1 percent in 2017 and 3 percent in 2018.
  - Increasing contributions from domestic demand as adjustment to the bust in commodity prices and decline in mining investment advances; export growth expected to slow as initial boost from new mining capacity moderates.
- New Zealand:
  - Growth expected at 3.1 percent in 2017 and 2.9 percent in 2018, supported by construction pipeline, migration inflows, and improved dairy export prices.
- Hong Kong SAR:
  - Growth expected to recover to 2.4 percent in 2017 and 2.5 percent in 2018.
  - External conditions to remain soft with a somewhat faster pace of tightening in monetary conditions aligned with changes in U.S. monetary policy expectations.
- ASEAN economies (selected projections):
  - Indonesia: growth projected at 5.1 percent in 2017 and 5.3 percent in 2018; private investment expected to gradually recover with higher commodity prices.
  - Malaysia: growth projected at 4.5 percent in 2017 and 4.7 percent in 2018; domestic demand main driver, small drag from net exports in 2017 disappearing in 2018; higher inflation, high household debt, and macroprudential policy could hold consumption back.
  - Thailand: growth projected at 3 percent in 2017 and 3.3 percent in 2018; public investment expected to increase, crowding in private investment and imports, while exports strengthen—overall net exports expected to be a bigger drag.
  - Philippines: growth projected at 6.8 percent in 2017 and 6.9 percent in 2018, led by strong private domestic demand and a modest recovery in exports.
  - Singapore: growth projected at 2.2 percent in 2017 and 2.6 percent in 2018, supported by recovering private domestic demand.
  - Vietnam: growth projected at 6.5 percent in 2017 and 6.3 percent in 2018, owing to healthy domestic demand, a rebound in agricultural production, and strong external demand.

*International Monetary Fund | April 2017*

### 1.  PREPARING fOR ChOPPy sEAs

### 1.  PREPARING fOR ChOPPy sEAs

### Growth outlook and country highlights
- Frontier economies and small states are expected to rebound in 2017 and 2018 owing to better global trade growth and a recovery in commodity prices.
- Sri Lanka: GDP growth is projected to recover to 4.5 percent in 2017 and to 4.8 percent in 2018 as growth in manufacturing, construction, and services is expected to offset the drought-stricken agriculture sector. Under the IMF’s Extended Fund Facility (EFF), 2016 fiscal performance has been solid, but the net international reserves fell short of the target.
- Mongolia: Growth is expected to remain subdued in 2017 on account of large fiscal consolidation, but the strengthening of policies under the EFF, along with some major expected mining developments, should boost growth substantially in 2018.
- Pacific island countries: Growth in the Pacific island countries is projected to rebound in 2017 and 2018 owing to the recovery in commodity prices for gas and oil exporters, including Papua New Guinea. Fiji is expected to have a strong recovery from last year’s cyclone. Tourism and fishery activities are expected to continue to support growth in the region.

### Inflation, output gaps, and current account
- Headline inflation is projected to rise to 2.9 percent in 2017 and 2018.
- Despite the recovery in commodity prices and the increase in producer price inflation, consumer price inflation is expected to remain low across most of the region given generally well-anchored inflation expectations and relatively low pass-through.
- Estimated output gaps for some regional economies suggest there is sufficient slack across the region, which will put downward pressure on inflation; however, inflation in countries where output gaps are nearly closed and credit gaps remain significantly large may face upside risks.
- In frontier economies with the highest inflation rates in the region, such as Myanmar and Nepal, inflation is expected to remain within single digits.
- Current account: The regional current account is expected to decline to 2.1 percent of GDP in 2017 and further to 2 percent of GDP in 2018. Drivers include the recovery in commodity prices and a pickup in import growth as domestic demand remains strong.
  - China’s current account surplus is expected to decline further, driven by the lower trade surplus and an increase in the services deficit.
  - India’s current account deficit is expected to widen as domestic demand strengthens further and commodity prices gradually rebound.
  - Japan’s current account is projected to rise due to a stronger goods trade balance.

### Monetary and fiscal stance
- Monetary policy: Policy interest rates are generally low in nominal and real terms. With the exception of India, real rates are below 1 percent in all major regional economies and are negative in a number of them.
- Policy reaction: In several economies, nominal policy rates are broadly in line with or slightly below the levels implied by augmented Taylor rules (which include exchange rates and foreign interest rates).
- Fiscal policy: Fiscal stimulus, measured by changes in the cyclically adjusted fiscal balances, is expected to increase in 2017 in several economies in the region, including China, the Philippines, Singapore, and Thailand.
  - In other major economies, the fiscal stance, while still accommodative, is expected to be slightly less supportive of growth, including in India and Vietnam.
  - In 2018, fiscal stimulus is projected to increase in Indonesia, the Philippines, and Thailand.
  - In other economies, such as Japan and China, fiscal policy is projected to be less supportive of growth as the effects of fiscal stimulus fade.

### Risks to the outlook — balance lies to the downside
- Major downside risks:
  - A possible shift toward protectionism in major trading partners.
  - Continued tightening in global financial conditions triggering capital flow volatility, especially given balance sheet weaknesses in some economies.
  - A bumpier-than-expected transition in China with large spillovers.
  - Geopolitical tensions and idiosyncratic political problems.
  - Medium-term secular headwinds: population aging and limited productivity convergence.
- Upside risks:
  - Stronger global activity resulting from larger policy stimulus than currently projected, especially in the United States.
  - Stronger U.S. fiscal stimulus could boost Asian exports and increase growth in the region, unless offset by tighter financial conditions or protectionist trade policies.
  - Short-term upside also stems from stronger-than-expected policy easing in the United States.
- Tighter global financial conditions:
  - Expansionary U.S. fiscal policy could lead to higher U.S. inflationary pressures and may require a tighter-than-expected monetary stance, including a steeper path for future increases in the federal funds rate and further decompression of the term premium.
  - A substantial tightening of financial conditions—significant U.S. dollar appreciation and higher interest rates—could have large negative spillovers for Asia, particularly economies with high dollar-denominated corporate and sovereign debt.
  - Capital outflows, higher financing costs, and fiscal-sustainability concerns could push countries into an unwarranted tight policy mix and amplify macroeconomic and financial-stability risks.
  - Corporate bond stress could feed back into the banking system because corporate bonds are largely held by domestic banks.
- Relative resilience and heterogeneity:
  - On average, Asian emerging market economies appear relatively better positioned to deal with external shocks than emerging markets in other regions, with stronger external buffers and lower external financing needs on average.
  - The banking system’s capital adequacy ratio is lower than in other regions but only by a small margin.
  - Large intra-region heterogeneity exists: for example, external financing requirement in Malaysia is relatively high; foreign share of nonfinancial corporate debt in Indonesia is relatively high.
  - In scenarios with rising global risk premia or rising economic nationalism, corporate vulnerabilities in China and India would significantly worsen.

### Deglobalization and trade/labor linkages
- Deglobalization is a substantial downside risk: disruptions to global trade, capital, and labor flows resulting from inward shifts in policy would deter investment, reduce productivity, and lower global growth.
- Asia’s vulnerability to trade shocks is elevated by high trade openness ratios and significant participation in global value chains; more protectionist trade policies would generate significant negative impacts.
- A disruption of labor flows could reduce remittance inflows to emerging Asian countries:
  - Remittances from the Gulf Cooperation Council, the euro area, the United Kingdom, and the United States collectively accounted for about three-quarters of total remittance inflows to Asian emerging markets in 2015.
  - Remittances were particularly significant in Nepal (almost 25 percent of GDP), followed by the Philippines, Sri Lanka, Bangladesh, and Vietnam (4.5 to 7 percent of GDP).
  - As of end-2013, emerging Asia’s emigrants to these economies accounted for about 57 percent of their total population of migrants abroad; more restrictive immigration policies in traditional destination countries could reduce migration outflows and diversify destinations to other economies, including within Asia.

### China’s slowdown and spillovers
- China’s growth is slowing as it transitions to a more consumption-based economy, yet China continues to drive about one-third of global growth.
- Sustained progress on reforms and reining in vulnerabilities in China would reduce downside risks, boost confidence, and lift investment in trading partners.
- While China’s transition is expected to be positive over the medium term, the near-term growth slowdown will generate large spillovers that vary by country and region; some spillovers may be negative.

*Source: International Monetary Fund | April 2017*

### 1. Emerging Asia: Remittance Inflows from Selected Sources

### 1. Emerging Asia: Remittance Inflows from Selected Sources

### Remittance inflows and migrant stock (Figure 1.30)
- Remittance shares (percent of total remittances to emerging Asia): 23.7%; 3.2%; 5.6%; 10.2%; 28.5%; 28.8%; 34%
- Migrant stock shares (percent of total migrant stocks): 21%; 3%; 6%; 9%; 27%
- Sources: World Bank Bilateral Remittances Matrix, 2015; World Bank Bilateral Migration Matrix, 2013; and IMF staff estimates.
- Note: Recipient and source Asian countries consist of China, India, Indonesia, Malaysia, the Philippines, Sri Lanka, Thailand, and Vietnam; Gulf Cooperation Council countries consist of Bahrain, Kuwiat, Oman, Qatar, Saudi Arabia, United Arab Emirates.

### Spillovers from China’s rebalancing and slowdown
- Short-term effects:
  - Reform and rebalancing are projected to pull China’s GDP growth below the no-reform scenario (IMF 2016).
  - Spillovers from rebalancing are negative for most countries in the short term.
- Medium-term effects:
  - Spillovers turn positive as reform and successful rebalancing from investment to consumption put China on a stronger and more sustainable footing and bring about growth dividends for both China and the world.
- Transmission channels:
  - Trade and commodity price channels are the main spillover routes.
  - Import intensity: investment ~25 percent; consumption ~15 percent.
  - China accounts for about 40 percent of global demand for metals and about 10 percent for crude oil demand.
  - IMF staff analysis suggests China’s rebalancing accounted for between one-fifth and one-half of the declines in broad commodity price indices between mid-2011 and mid-2015, with marked differences across commodities.
- Financial spillovers:
  - Financial spillovers from China have increased significantly since the global financial crisis, in particular in equity and foreign exchange markets, magnified by direct trade exposures.
  - With increasing vulnerabilities from credit-driven growth and high leverage, financial market spillovers become an increasingly important channel, especially in downside scenarios.

### Geopolitical, climate, and other risks
- Key risks:
  - Escalation of geopolitical tensions that could hurt tourism, FDI, and trade.
  - Climate change and natural disasters, and withdrawal by global banks of correspondent banking relationships (de-risking).
- Recent environmental shocks:
  - At least one country in the region hit by a severe cyclone in each of the past three years: Tonga in 2014, Myanmar and Vanuatu in 2015, and Fiji in 2016.
  - 2015 earthquake in Nepal as an example of severe disruption.
- World Risk Index, 2016 (selected figures):
  - Pacific island countries average: 19
  - Nonsmall states average: 7
  - Small states (excl. PICs) average: 8
  - Example country exposures listed: Vanuatu, Tonga, Philippines, Guatemala, Bangladesh, Solomon Islands, Brunei Darussalam, Costa Rica, Cambodia, Papua New Guinea, El Salvador, Timor-Leste, Mauritius, Nicaragua, Guinea-Bissau, Fiji

### Policy recommendations — macro and structural
- General stance:
  - Policies should remain flexible and focused on addressing vulnerabilities and rebuilding buffers, reducing domestic and external imbalances, safeguarding against external shocks, and preserving gains from trade integration.
  - Structural reforms are needed to deal with demographic transition and to boost productivity.
- Monetary policy:
  - Generally remain accommodative given inflation below target and slack in most economies.
  - Some central banks could have room to lower interest rates if growth slides, provided external stability is not compromised (example countries: Malaysia and Thailand).
  - Some central banks should stand ready to raise policy rates if inflationary pressures gather pace (example countries: India, Indonesia, and Vietnam).
  - Weigh benefits of prolonged accommodation against risks for inflation, asset prices, and domestic financial conditions; enhance macroprudential settings where appropriate (example: China).
  - Tightening may be warranted in case of large capital outflows and rapid exchange rate depreciations to address balance of payments pressures.
- Fiscal policy:
  - Fiscal support should be considered to support and complement structural reform efforts.
  - Fiscal action should consider fiscal space and the need to support demand and external rebalancing consistently (example countries: Korea and Thailand).
  - Delivering on medium-term fiscal consolidation plans remains critical where debt levels are high and/or fiscal credibility needs enhancement (example: EFF aims at restoring debt sustainability in Mongolia and improving debt trajectory in Sri Lanka).
  - Consolidation should be accompanied by adjustments to spending composition to allow for infrastructure and social spending; in China, emphasis should be on reducing public investment in favor of consumption.
  - Real growth in public spending has been high across most of the region, suggesting room for gradual adjustment, including in rigid components such as wages.
- Structural reforms:
  - Move steadfastly to implement growth-enhancing reforms to capitalize on solid growth momentum and policy space.
  - Structural reforms aim to rebalance demand and supply, reduce external imbalances, mitigate vulnerabilities, increase economic efficiency and potential growth, reduce poverty and inequality, and foster inclusive growth.
  - Complementary policies may be needed to mitigate distributional effects of reforms (see Box 1.5 for Myanmar example).
  - Reforms can also address climate change and environmental issues, particularly in fossil-fuel-reliant large countries.
- Financial stability and external volatility:
  - Exchange rates should generally remain the first line of defense against sudden tightening in global financial conditions, shifts toward protectionism, or a bumpier-than-expected transition in China.
  - Judicious foreign exchange intervention can be deployed to prevent or mitigate disorderly market conditions, provided sufficient reserve buffers and not used to resist movements reflecting fundamentals.
  - Effective communication of policy goals can bolster confidence and lower market volatility.
  - Robust macroprudential frameworks are required to mitigate systemic risks from high corporate and household leverage and rising interest rates.
  - Use macroprudential tools to contain risks from rising house prices and household leverage and to increase resilience to shocks, including capital flow reversals.
  - Monitor net foreign currency positions and foreign currency maturity gaps closely; consider capital flow management measures if volatility increases systemic risk, but not as a substitute for macroeconomic adjustments.

### Demographic transition and productivity priorities
- Aging at relatively low per capita income levels poses challenges; policies needed to protect vulnerable elderly and prolong strong growth.
- Structural reforms in labor markets, pension systems, and retirement systems should be adopted early to ensure debt sustainability.
- Productivity-enhancing reforms are critical:
  - Advanced economies: improve effectiveness of research and development spending and raise productivity in services.
  - Emerging and developing economies: increase absorptive capacity and domestic investment to capitalize on FDI inflows; increase education and human capital.

### Box 1.1 — India’s currency withdrawal and economic impact
- Action taken:
  - On November 8, 2016, the Government of India withdrew the legal tender status of all existing 500 and 1,000 rupee banknotes, effective the next day.
  - Notes affected had a total value of about 15 trillion rupees, which accounted for about 86 percent of all cash in circulation.
  - New series of 500 and 2,000 rupee banknotes announced; supply was insufficient in the months following the initiative.
- Cash economy indicators:
  - Currency in circulation in India stood at about 12 percent of GDP at end-2015.
  - Cash accounted for about three-quarters of the narrow money base.
  - Average number of transactions per Indian made with payment instruments in 2015: 11 transactions.
  - Number of payment cards per capita data (2015): 0.0; 1.0; 0.5; 0.5; 1.4; 1.7; 2.2; 2.4; 3.6; 2.5; 2.0; 1.5; 3.0; 3.5; 4.0 (figure labels by country: India, Mexico, Russia, Turkey, Brazil, China*).
  - Number of transactions with payment instruments per capita (2015) example values: 0; 40; 20; 11; 32; 17; 53; 106; 142; 100; 80; 60; 120; 140; 160 (figure labels by country: India, China*, Russia, Turkey, Brazil, Mexico).
- Economic impacts and indicators:
  - Purchasing Manager’s Index for services fell from 55 in October 2016 to 43 in November 2016.
  - Growth of credit to the nonfood private sector decelerated from 9 percent at end-October 2016 to 4 percent by end-December 2016.
  - Consumer goods component of the index of industrial production declined by about 7 percent in December 2016; production of consumer durables fell by 10 percent.
  - Domestic sales of motor vehicles declined by 20 percent in December 2016 compared to December 2015, with largest drop in three-wheel and two-wheel passenger vehicles.
  - Number of new investment projects announced during October–December 2016 quarter was the lowest in over a decade; combined value was about one-half of the average recorded during the previous two years.
  - Remonetization progress: about 75 percent of the predemonetization level of currency in circulation was restored by late March.
- IMF staff analysis of growth impact:
  - Cash shortages are likely to slow FY2016/17 growth by about 4/5 of 1 percentage point and FY2017/18 growth by about ½ of 1 percentage point.
  - The currency shortage was modeled as a temporary tightening of monetary conditions that gradually unwinds through early 2017; GDP growth expected to slow in the second half of FY2016/17, before gradually rebounding during FY2017/18.
- Sources and notes:
  - Prepared by Volodymyr Tulin. Source: Bank for International Settlements. *China data are for 2014.

*International Monetary Fund | April 2017*

### Box 1.1 (continued)

### Box 1.1 (continued)

### India: Currency Withdrawal and Exchange Initiative — Near-term Risks and Medium-term Opportunities
- Near-term domestic risk: disruptions from the currency withdrawal remain a key domestic risk in India, in part as the near-term adverse economic impact of accompanying cash shortages remains difficult to gauge.
- Fiscal gains:
  - Bank deposits of large amounts (above US$4,000) were expected to attract high scrutiny from the Indian tax authorities.
  - With only about 1 percent of the Indian population paying personal income taxes, the scope for broadening the tax base is clearly large.
  - Unreturned cash could produce a one-off revenue gain for the Reserve Bank of India that can enable an increased dividend transfer to the Government of India; any such windfall revenue would need to be clearly established, should be only realized once, and should be absorbed prudently and preferably in a non-recurring manner, for example through greater capital injections to public sector banks.
- Banking sector liquidity:
  - The increase in banking system liquidity as a result of the currency exchange initiative has been massive and can reduce banks’ funding costs and thereby lead to a decline in bank lending rates.
  - The weighted average lending rate of banks on new loans declined by 56 basis points during November 2016 to January 2017.
  - Authorities should remain vigilant to risks, including potential further buildup of nonperforming loans, elevated corporate sector vulnerabilities, and ensure prudent support to affected sectors.
- Digitalization and de-cashing:
  - Over the past few years, 250 million previously unbanked Indians have been provided with a bank account.
  - About 350 million Indians do not yet have cell phones, and only 250 million people own smartphones.
  - Important technological milestones include rollout of a unique identification number (Aadhaar), adoption of know-your-customer technologies, and rollout of the Unified Payment Interface (an instant virtual fund transfer between two bank accounts using a mobile platform) accompanied by e-payment and point-of-sale technologies.

### Global Financial Spillovers to ASEAN-5: Markets, Channels, and Growth Impacts
- Market developments:
  - Markets in Indonesia, Malaysia, the Philippines, Singapore, and Thailand (ASEAN-5) underwent significant corrections since the U.S. election, though they generally performed better than other emerging markets since the 2013 taper tantrum.
  - Following the U.S. election, ASEAN-5 experienced capital outflows, exchange rate depreciations vis-à-vis the U.S. dollar, and 10-year sovereign bond yields rising in most countries.
- Key macro-financial transmission channels identified:
  - Global risk aversion: largely impacts portfolio capital flows and asset prices.
  - U.S. interest rates: mainly affects bond yields and credit conditions.
- Economic impact:
  - Capital outflows and weaker asset prices have historically been the largest exogenous driver of business cycle fluctuations in the ASEAN-5 (preliminary Bayesian vector autoregression).
  - Exchange rate depreciation can cushion tightening domestic financial conditions, but rise in domestic bond yields (closely linked to U.S. rates) could lower property prices (dampen construction) and soften domestic demand.
  - Balance sheet impact of exchange rate depreciation may outweigh net export benefits in countries with high corporate leverage and foreign exchange exposures.

### Rising Household Debt in Asia: Levels, Risks, and Drivers
- Levels and recent increases:
  - Household-debt-to-GDP ratio in 2015 ranged from 10 percent of GDP in India to 124 percent of GDP in Australia.
  - Between 2007 and 2015, the household-debt-to-GDP ratio increased by more than 20 percentage points of GDP in Thailand, Malaysia, and China.
  - The rise was more than 15 percentage points of GDP in Australia, Korea, and Hong Kong SAR.
  - Total household debt currently stands above 60 percent of GDP in most Asian economies, with the exception of China, India, and Indonesia.
- Risks from high and rising household debt:
  - Falling house prices could lower collateral values, weaken household and bank balance sheets, tighten credit availability, and weigh on consumption and domestic demand through a wealth effect.
  - Rapid increases in household debt since 2007 seem to be associated with lower future income growth in many countries.
- Drivers and empirical framework:
  - Empirical single-equation framework for an unbalanced panel of 19 countries (including six Asian countries) over 1973–2015:
    - ΔDit = αΔDit–1 + βXit–1 + γIit–2 + νi + ηt + eit, where ΔDit denotes change in household debt in percent of GDP.
    - Xit–1 includes changes in the short-term interest rate and real per capita GDP growth and its level, and Δ Top 1% income share; explanatory variables lagged by one year; inequality variable included with a two-year lag.
  - Key empirical findings (fixed-effects estimations; country and time fixed effects included):
    - Positive and significant coefficient on lagged dependent variable (examples from Table 1.3.1): 0.565*** (standard error 0.0435) in specification (2); 0.574*** (0.0459) in specification (6).
    - Δ short-Term Interest Rate, t-1: −0.141** (0.0619) in specification (1); −0.124** (0.0597) in specification (6).
    - Per Capita GDP, t-1: 0.0383** (0.0158) in specification (2); 0.0383** (0.0159) in specification (6).
    - Per Capita GDP Growth, t-1: 0.257*** (0.0522) in specification (2); 0.264*** (0.0543) in specification (6).
    - Δ Top 1% Income share, t-2: 0.390*** (0.143) in specification (2); 0.422*** (0.132) in specification (6).
    - Observations vary across specifications (for example, 416, 438, 180, 430); R-squared ranges from 0.518 to 0.587 across reported specifications.
  - Interpretation:
    - Rising income and cheaper credit have been associated with increases in household debt.
    - Rising income inequality has been associated with an increase in household indebtedness.
    - Asia does not seem to differ from other regions with regard to these key drivers.
- Policy implications:
  - Tackle income inequality.
  - Strengthen resilience to risks from rising household indebtedness by enhancing buffers and tightening prudential macro policies where needed.

### Potential Policy Changes in the United States and Implications for Asia
- Macroeconomic policy mix (as assumed in April 2017 World Economic Outlook):
  - Shift toward more expansionary fiscal policy and tighter monetary stance in the United States relative to October 2016 World Economic Outlook.
  - Fiscal expansion could come mainly from anticipated changes in U.S. federal government tax policies, including lower individual and corporate income tax rates.
  - U.S. monetary policy would tighten in response to higher demand and inflation prospects, leading to normalization of the U.S. term premium and an appreciation of the U.S. dollar.
  - Stronger U.S. demand would benefit Asian exporters provided financial markets remain orderly; if fiscal expansion is not sufficiently productive, spillovers to Asia could become negative.
- Corporate income tax reform implications:
  - Proposed U.S. reforms discussed include reducing rates, simplifying the system, a one-time tax rate reduction for repatriation of U.S. corporate profits overseas, and proposals to transform to a destination-based cash flow tax (DBCFT) system (immediate expensing of capital investment; eliminating deduction of net interest payments; deduction of earnings from exports and elimination of deduction of imported inputs).
  - Short-term: real effective U.S. dollar appreciation with introduction of a border tax adjustment could lead to:
    - For Asian economies with flexible exchange rates: higher consumer price inflation via higher import prices and higher external debt burden.
    - For economies pegged to the U.S. dollar or dollarized: increased downward pressures on foreign exchange reserves and domestic prices.
    - Trade balance could worsen absent sufficient exchange rate depreciation.
  - Longer term: incentive for U.S. companies to shift production or income to lower-tax-rate jurisdictions outside the United States would diminish; Asian supply chains linked to the United States (notably in China, Malaysia, and Vietnam) could weaken as FDI inflows into Asia slow.
  - The one-time tax rate cut on repatriated U.S. corporate profits could trigger capital outflows from deposit countries, tighten offshore dollar funding conditions, and accelerate U.S. dollar appreciation.
- International trade policies:
  - U.S. trade policy focus expected to pivot toward greater protection of domestic players, more active use of trade remedy and enforcement tools, and favoring bilateral trade negotiations over multilateral ones (illustrated by withdrawal from the Trans-Pacific Partnership).
  - Increased tension and uncertainty in the global trade climate could negatively affect Asia’s exports to the United States (for example, China, Japan, Korea, and Taiwan Province of China).
  - Over the long run, a slowdown in global trade and FDI due to U.S. pullback from cross-border economic integration could hinder technology transfers through these linkages.

*Source: Regional Economic Outlook: Asia and Pacific, International Monetary Fund | April 2017 — Box 1.1 (continued).*

### Box 1.4 (continued)

### Box 1.5. Myanmar: Macroeconomic and Distributional Implications of Financial Reforms

### Context and objectives
- The box analyzes the potential impact on income inequality of Myanmar’s financial sector reform, a priority for the government.
- A financial sector development strategy has been developed with the assistance of the IMF and the World Bank, and a financial inclusion road map has been launched.
- Key institutional/structural features and challenges described:
  - The Central Bank of Myanmar continues to finance a significant portion of the fiscal deficit, generating inflation and exchange rate depreciation pressures while placing a disproportional burden on the poor.
  - Administrative controls on interest rates—a floor on deposit rates and a ceiling on lending rates—have led to financial suppression amid relatively high inflation.
  - Access to basic financial services is very low, with over 75 percent of adults not having a bank account and the majority of the population relying on unregulated lenders, often at very high costs.
  - Agriculture accounts for 30 percent of GDP and employs more than half of the population but receives only a small fraction of total outstanding bank loans.
  - Small and medium-sized enterprises are underserved by the formal financial system.

### Policy experiments analyzed
Four policy experiments were conducted using a dynamic stochastic general equilibrium model tailored to Myanmar:
- 1. Financial reform/liberalization: The government reduces central bank financing and pursues gradual liberalization of interest rates
- 2. Financial inclusion: Policy changes in the “financial reform/liberalization” scenario plus easier rural access to private credit
- 3. Higher infrastructure investment: Policy changes in the “financial inclusion” scenario plus the channeling of the reform-generated higher tax revenues toward economy-wide infrastructure investment
- 4. Higher infrastructure investment in agriculture: Policy changes in the “financial inclusion” scenario plus the channeling of the reform-generated higher tax revenues toward rural infrastructure investment

### Key quantitative and qualitative findings
- Growth effects
  - Financial liberalization (reducing central bank financing and allowing higher real interest rates) would increase savings, private credit, and ultimately economic growth (Figure 1.5.1).
  - Mechanism: Higher nominal interest on savings and lower inflation raise real interest on savings, motivating households to save more; increased savings reduce the real interest rate on private credit, spurring investment and industrial expansion, boosting labor demand and urban wages, and inducing rural-to-urban migration that raises overall economic activity.
- Distributional effects
  - Financial liberalization would boost growth and reduce poverty overall, but may increase certain dimensions of inequality such as intra-rural and intra-urban income inequality (Figures 1.5.2 and 1.5.3).
  - The increase in inequality reflects the tendency for financial liberalization to disproportionately benefit those who already have financial access. Even when credit access improves generally, the rural households that benefit most from increased credit access are usually those that are better-off, typically with larger land holdings, high productivity, and better managerial skills.
  - An increase in infrastructure investment financed by reform-generated revenue—even if targeted toward rural areas—can lead to increased inequality within the rural sector despite likely improvement in income distribution between rural and urban areas.
- Poverty effects
  - Financial liberalization is associated with reductions in poverty overall, though Figure 1.5.3 shows heterogeneous changes across national, rural, and urban poverty rates (total change, percentage points).
- Sectoral implications
  - Investment rises and the industrial sector expands under liberalization, increasing urban labor demand and wages and encouraging migration from rural areas.
  - Agriculture, despite its importance (30 percent of GDP; employs more than half of the population), is currently underserved by bank lending and may not automatically benefit evenly from broader financial reforms.

### Policy implications and recommendations
- Complementary measures are critical: Financial liberalization can boost growth and reduce poverty but may worsen intra-sectoral inequality without changes to the institutional setup and targeted policies.
- Where equality is an important policy objective, reforms such as financial liberalization need to be supported by policy measures that target disadvantaged groups. Such measures may include:
  - Fiscal measures that directly help disadvantaged groups.
  - Sound financial policies and targeted financial inclusion interventions to ensure the neediest sectors capture the benefits of increased credit access.
  - Careful design of infrastructure spending to avoid exacerbating within-sector inequality (for example, rural-targeted infrastructure may still increase intra-rural inequality if benefits accrue unevenly).
- The modeling highlights the importance of explicitly considering distributional outcomes when designing and sequencing financial-sector reforms.

*This box was prepared by Yiqun Wu, Sandra Valentina Lizarazo Ruiz, and Marina Mendes Tavares. Source: IMF staff estimates.*

### 2.  Asia: At Risk of Growing Old before Becoming Rich?

### 2.  Asia: At Risk of Growing Old before Becoming Rich?

### Main policy implications
- Adapting to aging could be especially challenging for Asia, as populations living at relatively low per capita income levels in many parts of the region are rapidly becoming old. Policies aimed at protecting the vulnerable elderly and prolonging strong growth take on a particular urgency in Asia.
- Given these low income levels, it is important to adapt macroeconomic policies early on before aging sets in. This may include securing debt sustainability and monitoring potential changes in monetary transmission owing to aging.
- Specific structural reforms—which fiscal space can support—can help address these challenges:
  - Labor market reforms: promoting labor force participation of women and the elderly, guest worker programs, and active labor market policies.
  - Pension reforms: automatic adjustment mechanisms and minimum pension guarantees.
  - Retirement system reforms: new financial products to reduce precautionary savings and increase the availability of “safe assets.”
- These reforms could be further supplemented by productivity-enhancing reforms (for example, through research and development and education).

### Demographic trends in Asia
- Asia is undergoing a demographic transition marked by slowing population growth and aging, mainly reflecting declining fertility rates since the late 1960s and to a lesser extent rising life expectancy.
- The population growth rate is already negative in Japan and is projected to fall to zero for Asia by 2050.
- The working-age population share is at its peak now and projected to decline over coming decades.
- The share of the population age 65 and older will increase rapidly and reach close to 2½ times the current level by 2050.
- East Asia is projected to be the world’s fastest-aging region, with its old-age dependency ratio roughly tripling by 2050.
- Three demographic groups (based on World Bank 2015 approach and UN 2015 medium-fertility scenario) and major economies:
  - Post-dividend: China, Hong Kong SAR, Japan, Korea, Thailand. Japan: old-age dependency ratio of 43 percent at the end of 2015, rising to 71 percent by the end of 2050. Singapore projected to transition to post-dividend status by 2030.
  - Late-dividend: Malaysia, Vietnam, Australia, New Zealand, Singapore (in 2015 due to immigration).
  - Early-dividend: India, Indonesia, Philippines. Fertility rates projected to remain above 2.1 children per woman for India and Indonesia until 2030 and beyond that for the Philippines. Indonesia projected to transition to late-dividend status by 2030.
- Migration effects:
  - Immigration has been sizable in Australia, New Zealand, Hong Kong SAR, and Singapore and is projected to substantially slow the decline of working-age populations in those economies.
  - Emigration of working-age people is notable for the Philippines but small relative to population size. For China, Japan, Korea, and ASEAN members, net migration is relatively small.
- Speed of aging:
  - The number of years for the old-age dependency ratio to increase from 15 percent to 20 percent: 26 years in Europe and more than 50 years in the United States; in many Asian countries (China, Japan, Korea, Thailand, Singapore, Vietnam) the same transition has taken or will take less than 10 years.
  - Implication: less time to adapt policies and risk of becoming old before becoming rich.
- Per capita income at the peak of working-age population share:
  - Except for Japan and Australia, per capita income in major Asian countries stands at significantly lower levels than those reached by mature advanced economies at the same stage of the aging cycle (figure-based evidence cited).

### Quantitative demographic indicators (selected)
- Global impact of demographic-driven surplus changes: about 0.1 of a percentage point of global GDP over the next decade.
- Japan old-age dependency ratio: 43.3 in 2015; projected 71.0 by 2050 (Table 2.2 values: 2000–2050 series include 25.2, 29.9, 36.0, 43.3, 48.3, 50.6, 53.1, 57.0, 63.8, 68.1, 70.9).
- Hong Kong SAR old-age dependency ratio series (2000–2050): 15.3, 16.5, 17.2, 20.6, 26.5, 35.1, 43.7, 50.1, 55.6, 60.4, 64.6.
- Korea old-age dependency ratio series (2000–2050): 10.2, 12.7, 15.0, 18.0, 22.2, 29.4, 37.6, 46.1, 54.4, 60.7, 65.8.
- Singapore old-age dependency ratio series (2000–2050): 10.3, 11.3, 12.2, 16.1, 21.4, 28.6, 36.5, 43.7, 51.1, 57.2, 61.6.
- China old-age dependency ratio series (2000–2050): 9.7, 10.4, 11.1, 13.1, 17.1, 20.4, 25.3, 32.7, 39.6, 43.0, 46.7.
- Selected other country series are provided in Table 2.2 (Malaysia, Indonesia, India, Philippines, Thailand, Vietnam, Australia, New Zealand) with decadal values through 2050 as in the source.

### Growth implications of demographic trends
- Asia benefited from a substantial demographic dividend in past decades; rapid aging is set to create a demographic “tax” on growth in several countries.
- Analysis framework (Amaglobeli and Shi 2016 template; UN medium-fertility scenario including migration):
  - Baseline assumptions:
    - Unchanged total factor productivity (TFP) growth (based on the historical average).
    - Unchanged age- and gender-specific labor force participation rates (and employment rates).
    - Constant capital-to-effective-labor ratio (investment adjusts over time to labor, where labor is in efficiency units).
  - The baseline compares estimated output under UN medium-fertility scenario to a hypothetical status quo with constant population size and age structure. Also considers UN zero-migration scenario for migration impact.

### Impact of the labor force on economic growth (baseline estimates, average 2020–50)
- Key findings (percentage point impact on real GDP growth; average, 2020–50):
  - Demographic trends become strong headwinds for post-dividend countries:
    - Japan: impact could reduce the average annual growth rate by almost 1 percentage point.
    - China, Hong Kong SAR, Korea, Thailand: growth impact could be between one-half and three-quarters of a percentage point.
    - Singapore (transitioning to post-dividend by 2030): estimated overall impact close to zero.
  - Early- and late-dividend countries could enjoy a substantial demographic dividend:
    - Philippines: close to 1½ percent per year demographic dividend.
    - New Zealand: about ½ percent per year demographic dividend.
    - Note: reaping the dividend is not automatic and depends on policies to raise productivity and create quality jobs.
  - Migration effects:
    - Continued immigration in Australia, Hong Kong SAR, New Zealand, and Singapore could add between ½ and 1 percentage point to annual average growth.
    - Net emigration from Indonesia, the Philippines, and Vietnam has a small impact due to small relative size of emigration as a share of population.
    - Migration can reduce but cannot reverse the negative impact of aging. (Example: Australia would need to receive immigration equal to approximately — [text cut off in source].)
- Global aggregate:
  - Global impact indicator computed as purchasing-power-parity-weighted average reported in figure (exact weighted values shown in figure panels in source).

*Source: IMF staff estimates and projections based on Amaglobeli and Shi 2016 and United Nations 2015 (medium-fertility scenario); data and figures as presented in the source chapter.*

### 0.2 percentage point higher in the UN’s high-fertility scenario and

### areo0517 - 0.2 percentage point higher in the UN’s high-fertility scenario and

### Migration and workforce size
- Jaumotte, Koloskova, and Saxena (2016) estimate that a 1 percentage point increase in the share of migrants in the working-age population can raise GDP per capita over the long term by up to 2 percent by increasing labor productivity and, to a lesser extent, boosting investment.  
- The long-term UN assumptions on net migration rates for these countries range from 2.5 percent in New Zealand to 6 percent in Australia.  
- To maintain the same dependency ratio by 2030, one country would require 23 percent of the actual workforce as immigrants; the same immigration figure for Singapore would be 51 percent.  
- The positive impact of immigration on aggregate growth is partially eliminated when viewed on a per capita basis (notably for Hong Kong SAR and Singapore).

### Aging and Total Factor Productivity (TFP)
- Studies find differing evidence on aging’s impact on productivity: some find decline in worker productivity and innovation starting between ages 50 and 60 (Aiyar, Ebeke, and Shao 2016; Börsch-Supan and Weiss 2016; Feyrer 2007), while Acemoglu and Restrepo (2017) find no robust negative impact of aging on GDP per capita.  
- For a sample of Asian and European countries, an increase in the share of older workers (ages 55–65) is associated with a significant reduction in labor productivity growth.  
- Decomposition shows most of the slowdown is through weaker TFP growth: workforce aging is associated with lower annual TFP growth by 0.1 to 0.3 of a percentage point on average for Asia.  
- Figure 2.8 estimates that on average an older workforce is estimated to reduce growth by 0.2 percent per year, with the biggest impact for China (0.3 percent per year).  
- Workforce aging may be a substantial drag on future TFP growth for some countries but is likely second-order compared to baseline growth impact of changes in labor force size.

### Heterogeneity across occupations and countries
- Veen (2008) taxonomy: productivity of workers in physically demanding professions (factory workers, construction) declines with older ages, while productivity may increase with age in professions such as lawyers, managers, and doctors.  
- Countries with lower per capita income levels such as Thailand and Vietnam have a larger share of workforce in professions where productivity tends to decline with age—underscoring the importance of structural transformation.

### Labor Force Participation Rates (LFPRs) and policy scope
- Baseline estimates assume constant age-gender-specific LFPRs; LFPRs can change over time and be affected by policies.  
- In most OECD countries effective retirement age has increased, though modestly compared to life expectancy increases (Bloom, Canning, and Fink 2010).  
- In most Asian economies there is scope for greater female labor force participation, but unlocking this requires a comprehensive set of policies (Steinberg and Nakane 2012; Elborgh-Woytek and others 2013; Kinoshita and Guo 2015).  
- Figure 2.9: overall LFPRs in Asian economies have remained remarkably stable between 1990 and 2015, with notable subgroup shifts: female LFPRs increased in advanced economies but declined in China, India, Thailand, and Vietnam; male LFPRs declined in most countries; LFPRs for ages 15–24 dropped in all countries by up to a third; LFPRs for ages 55–64 increased in most countries.  
- A scenario allowing for a gradual increase in LFPR for all age and gender groups by 6 percentage points (based on Japan’s experience 1990–2015) could boost annual GDP growth by 0.2 to 0.3 of a percentage point and offset lower TFP growth due to aging.  
- Such LFPR changes are unlikely to counter baseline growth effects induced by changes in overall labor force.  
- A more ambitious scenario eliminating the employment gender gap could add ¼ of a percentage point to annual GDP growth for Japan and up to 1 percentage point for India by 2050 (Cuberes and Teignier 2016; Elborgh-Woytek and others, 2013; Khera 2016).  
- A 10 percentage point reduction in the gender inequality index is associated with almost 1 percentage point higher per capita GDP growth (Gonzales and others 2015).

### Aging and investment; capital-to-effective-labor assumption
- Baseline assumption: constant capital-to-effective-labor ratio.  
- Analysis finds workforce aging is associated with higher capital per worker (accounting for TFP), but the effect is economically small.  
- No statistically significant relationship found between old-age dependency ratio and capital per worker.  
- A constant capital-to-labor-ratio assumption is a reasonable approximation for the next three decades when countries are presumably on a balanced growth path.  
- Overall, demographic trends could reduce growth by ½ to 1 percentage point per year in absolute and per capita terms over the next three decades in post-dividend countries.  
- A 0.5 percentage point reduction in growth per year would reduce the level of GDP by 2050 by about 15 percent.

### External balance implications (EBA model results)
- The EBA model captures demographic impact using three variables: population growth, old-age dependency ratio, and aging speed (expected change in old-age dependency in 20 years).  
- Theoretical priors summarized (Table 2.3):
  - Population Growth → Savings: ↓ ; Investment: ↑ ; Current Account: ↓
  - Old-Age dependency → Savings: ↓↓ ; Investment: ↓ ; Current Account: Ambiguous
  - Aging speed → Savings: ↑ ; Investment: ↓ ; Current Account: ↑
- Empirical EBA results support priors on population growth and aging speed. Higher old-age dependency is positively associated with current account balance when aging speed is higher than the world average.  
- By 2020, Australia, Japan, and New Zealand will have higher old-age dependency ratios compared to the (GDP-weighted) world average. By 2030, Hong Kong SAR, Korea, and Singapore will also have higher old-age dependency ratios than the world average.  
- Several countries—Hong Kong SAR, Japan, Korea, Singapore, China, Thailand, and Vietnam—will have very high speeds of aging until 2030; Australia and New Zealand will have lower speeds of aging than the world average.  
- Over 2020–30, the EBA model suggests demographic trends are likely to exert upward pressure on current account balances in surplus countries such as Japan, Korea, and Thailand, and downward pressure in deficit countries, particularly New Zealand.  
- Demographics are projected to materially increase current account norms only for a select few countries in Asia; the total impact on global imbalances is limited.  
- Changes in population growth from 2020–30 are expected to have a relatively small contribution to changes in current account norms (less than 0.1 percent of GDP for the sample period).

### Capital flows and financial market implications
- Demographic factors are likely to strengthen current dynamics of capital flows: over 2020–30, changes in current account norms due to demographic trends are likely to be positively correlated with current account balances in 2015—surplus countries remain capital exporters; deficit countries remain capital importers.  
- Panel regression evidence indicates rising old-age dependency in post-dividend countries and falling youth dependency in early-dividend countries are both likely to put downward pressure on domestic real interest rates.  
- The downward pressure on real interest rates from demographic shifts diminishes for countries that are financially more open.  
- The partial equilibrium analysis underlying these results holds other macroeconomic variables fixed; broader interactions (fiscal balance, relative productivity, expected growth) could amplify or dampen the demographic impacts.

*International Monetary Fund | Regional Economic Outlook: Asia and Pacific (April 2017), excerpt.*

### 2.  AsIA: AT RIsK Of GROwING OLd bEfORE bECOMING RICh?

### 2.  AsIA: AT RIsK Of GROwING OLd bEfORE bECOMING RICh?

### Interest rates: recent trends and underlying forces
- Long-term bond yields have declined significantly in Europe and the United States; a similar trend is observed in Asia, particularly in Australia and Korea.
- World real interest rates have drifted down from around 4 percent in the late 1990s to about zero recently.
- The decline in real interest rates has reflected a decline in the natural rate of interest.
- Studies cited: Holston, Laubach, and Williams 2016; Lubik and Matthes 2015; Rachel and Smith 2015.
- In Asia:
  - Natural rates have fallen in advanced economies (Australia, Japan, and Korea).
  - Natural rates remain broadly stable and relatively high in emerging market economies that have yet to come under aging pressures.
  - In China, natural rates have fallen, but remain high relative to advanced Asian economies.

### Demographic drivers and theoretical channels
- Demographic factors highlighted: youth dependency, old-age dependency, and aging speed (Table 2.4).
- Mechanisms described:
  - Youth dependency:
    - As youth dependency rises, the transition working-age cohort saves less, capital-to-labor ratio falls, and interest rates rise.
    - Youth dependency is expected to fall drastically in early-dividend countries, such as the Philippines and India.
  - Old-age dependency:
    - As old-age dependency rises, savings fall; as the labor force shrinks, capital-to-labor ratio rises and investment falls.
    - The theoretical impact on interest rates is ambiguous; empirically, higher old-age dependency is found to reduce interest rates in the sample.
    - Old-age dependency is expected to rise relatively quickly in Hong Kong SAR, Korea, and Singapore.
  - Aging speed:
    - Higher aging speed implies a higher probability of survival, which, if not matched by later retirement, is likely to increase life-cycle savings.
    - Higher aging speed also lowers current investment, thereby reducing interest rates.
    - Aging speed is currently high and expected to fall in countries in late stages of the demographic transition; Japan is an exception where aging speed will continue to increase in the next decade.
- Table 2.4 summary (expected impact):
  - Youth dependency: savings ↓, investment ↑, interest rates ↑
  - Old-age dependency: savings ↓↓, investment ↓, interest rates Ambiguous
  - Aging speed: savings ↑, investment ↓↓, interest rates ↓

### Openness, empirical estimates, and projected impacts
- Openness matters: as an economy becomes more open, the impact of domestic demographic factors on interest rates diminishes; in a fully open economy the direct impact becomes zero (based on the Chinn-Ito index).
- Estimated coefficients (Table 2.5; standard errors in parentheses):
  - Youth dependency: 8.26 (1.95) — fully closed; 0 — fully open.
  - Old-Age dependency: 216.16 (5.51) — fully closed; 0 — fully open.
  - Aging speed: 229.26 (9.87) — fully closed; 0 — fully open.
- Quantitative projection:
  - Demographic trends could put downward pressure on interest rates by about 1 to 2 percentage points in the next decade, all else being equal.
- Country-specific tendencies:
  - For post-dividend countries (Korea and Thailand), rising old-age dependency is expected to depress interest rates.
  - For early-dividend countries (India and the Philippines), falling youth dependency is projected to reduce interest rates.
  - As aging speed slows in some countries (for example, China and Australia), interest rates are expected to increase because slowing aging speeds reduce savings.
  - Aging speed is projected to increase in currently young countries such as India and Malaysia, driving down their interest rates.

### Other asset valuations: stocks and real estate
- The “asset market meltdown” hypothesis postulates that retiree sell-off pressure could sharply reduce asset valuations; historical experience provides mixed evidence.
- Conceptual channels for stocks:
  - Demographics can affect expected stock returns via the risk-free rate and the equity risk premium.
  - Decline in youth dependency or increase in old-age dependency is expected to lower interest rates but may raise the equity risk premium due to a lower preference for risky assets; overall effect on stock returns is ambiguous.
- Empirical findings:
  - Lower youth (or higher old-age) dependency is associated with lower stock returns (interest rate channel dominates), but results are not statistically strong.
  - As with interest rates, the impact of domestic demographic factors on stock returns is partially offset in more financially open countries.
- Real estate:
  - Relationship with demographic variables is difficult to identify because housing is both an asset and a durable good.
  - Fall in interest rates (from demographic change) would mechanically raise house prices, but declining household formation could reduce housing demand.
  - Empirical links between demographics and real estate prices are weak.
  - Openness plays an insignificant role for real estate, likely reflecting the local nature of housing markets.

### Policy implications and recommendations
- For early-dividend countries (India, Indonesia, and the Philippines):
  - Main challenge: harness the demographic dividend and mitigate adverse spillovers from aging in the rest of Asia.
- For late- or post-dividend Asian countries:
  - Adapting to aging is urgent because rapid aging is occurring at relatively low per capita income levels.
  - Policies should focus on protecting vulnerable elderly and prolonging strong growth.
  - Adapt macroeconomic policies early before aging sets in and implement structural reforms in labor markets, pension systems, and retirement systems.
  - Productivity-enhancing reforms (for example, research and development and education) are important complements.
- Macroeconomic policy guidance:
  - Fiscal policy:
    - Introduce a credible medium-term fiscal framework to secure debt sustainability.
    - Shift the burden of taxes from labor to consumption.
    - Revamp the social safety net.
  - Monetary policy:
    - Study how monetary transmission may change with aging; transmission may work more through asset prices and household wealth rather than corporate borrowing costs.
    - Regular assessment of the neutral monetary stance by central banks is needed to avoid a potential tightening bias as natural interest rates decline.
    - Prolonged low interest rates may call for a strong macro-prudential framework to mitigate financial stability risks.
- Structural reforms — labor market:
  - Raise labor force participation, especially for women and the elderly:
    - Expand availability of child-care facilities, remove fiscal disincentives to dependents’ labor participation, and promote flexible employment.
    - Move from seniority-based to performance-based wage systems to incentivize firms to relax retirement age requirements and reduce labor market duality.
  - Encourage foreign workers through targeted guest worker programs and active integration policies (language training, job search assistance, recognition of credentials) to prolong demographic dividends or soften aging impacts.
  - Promote active labor market policies: improve affordable health care for mature workers and facilitate human capital upgrading and retraining.
- Structural reforms — pension systems:
  - Strengthen pension systems given rapid aging, related fiscal costs, and relatively low pension coverage.
  - Consider entitlement reform through automatic adjustment mechanisms that link retirement age (or benefits) to life expectancy to de-politicize reform and contain pension costs.

*International Monetary Fund | April 2017 — Chapter: 2.  AsIA: AT RIsK Of GROwING OLd bEfORE bECOMING RICh?*

### 2.  AsIA: AT RIsK Of GROwING OLd bEfORE bECOMING RICh?

### 2.  AsIA: AT RIsK Of GROwING OLd bEfORE bECOMING RICh?

### Retirement systems, financial products, and pension fund management
- Fiscal incentives to encourage voluntary savings (for example, tax deductions for long-term retirement savings) can help relieve long-term fiscal burdens.
- Raising pension coverage through minimum pension guarantees could:
  - provide a safety net for the vulnerable,
  - mitigate the impact of entitlement reforms,
  - reduce incentives for precautionary savings (Zaidi, Grech, and Fuchs 2006).
- Reforming the management of public pension funds:
  - Asia hosts some of the largest public pension funds in the world (OECD 2016).
  - Reducing home bias—along the lines of the recent Government Pension Investment Fund reforms in Japan—could help raise investment returns and secure more sustainable resources for aging societies.
- New financial products to support post-retirement dissaving and longevity risk insurance (for example, reverse mortgages and annuities) could lower the need for precautionary savings.
- Opportunities exist for cross-border risk sharing and financial integration within Asia; increasing the availability of “safe assets”—such as long-term government bonds or inflation-linked securities—can be attractive for pension funds and insurance companies (Groome, Blancher, and Ramlogan 2006).
- Financial integration in Asia remains low relative to trade integration: about 60 percent of Asia’s exports and imports are intraregional, while only 20 to 30 percent of cross-border portfolio investment and bank claims are intraregional (Regional Economic Outlook: Asia and Pacific, April 2015).

### Japan: demographic headwinds, growth, inflation, and monetary policy
- Demographic context:
  - Japan’s overall population started to shrink only after 2010; Japan’s working-age population has been declining since 1997.
  - The falling working-age population, together with the change in the overall labor force participation rate, reduced the Japanese labor force by over 7 percent between 1997 and 2016.
  - A simple growth decomposition suggests the negative impact on annual average growth has been about 0.3 of a percentage point.
- Aging and productivity:
  - Older workers may have higher productivity from experience; younger workers may benefit from better health, higher processing speed, and adaptability to technological change.
  - Estimates by Liu and Westelius (2016):
    - a 1 percentage point shift from the 30-year-old age group to the 40-year-old age group in Japan increased the level of total factor productivity by about 4.4 percent,
    - a similar shift from the 40-year-old to the 50-year-old age group decreased productivity by 1.3 percent.
- Labor force participation:
  - Government emphasis on raising participation of female and older workers.
  - Labor force participation rate for women rose from 63 to 65 percent between 2011 and 2016.
  - Labor force participation rate for workers ages 65 to 69 increased from 37 to 39 percent between 2011 and 2016.
- Inflation dynamics:
  - Hypothesis (Shirakawa 2012): demographic headwinds lower future growth and expected permanent income, causing cuts in current consumption and investment and triggering deflationary pressures.
  - Alternative view (Juselius and Takáts 2015): aging constrains labor supply while dissaving by retirees keeps demand stable, which may increase inflation; in Japan, repatriation of foreign savings could lead to currency appreciation offsetting inflationary effects (Anderson, Botman, and Hunt 2014).
  - Empirical result (Liu and Westelius 2016): a 1 percentage point increase in the old-age dependency ratio reduces the inflation rate by about 0.1 of a percentage point in Japan.
- Monetary policy effectiveness:
  - Secular stagnation channel (Summers 2013): structural excess savings and sluggish investment can depress the neutral interest rate, reducing monetary policy effectiveness and keeping inflation below target.
  - Japan’s demographic headwinds may have altered saving and investment propensities and contributed to prolonged low growth and low inflation.
- Policy implications:
  - Enhance labor supply by boosting female and older worker participation and allowing for more foreign labor.
  - Reduce labor market duality and increase private investment to improve growth prospects, monetary policy effectiveness, and fiscal sustainability.

*This box was prepared by Niklas Westelius.*

### Fiscal implications of demographic trends in Asia (projections and drivers)
- Under current policies, age-related public expenditures (pensions and health care) are projected to increase in many Asian countries, eroding public finances by up to 10 percentage points of GDP by 2050.
- In most cases, projected increases would be driven by pensions.
- Public pensions:
  - Projected pension expenditure increases depend on countries’ stage in demographic transition and pension system design (defined benefit versus defined contribution).
  - For several late- or post-dividend countries with defined benefit systems—China, Korea, New Zealand, Thailand, and Vietnam—public pension expenditures could rise by more than 5 percentage points of GDP by 2050, absent policy measures.
  - For early-dividend countries (India, Indonesia, and the Philippines), pension expenditures (as a percent of GDP) are expected to remain broadly unchanged.
- Health care:
  - Projected increases depend on the rise in old-age dependency ratios and the generosity of health systems.
  - Absent reforms, health care expenditures in post-dividend countries with relatively generous systems (Korea and Japan) are projected to increase by more than 3 percentage points of GDP by 2050.
  - In Japan, Nozaki, Kashiwase, and Saito (2014) show health care reforms could generate fiscal savings of 2 percent of GDP by 2030.
- Policy options:
  - Pensions: introduce automatic adjustment mechanisms (AAMs) linking retirement ages (or retirement benefits) to life expectancy, with adequate safety nets for the elderly poor; AAMs are limited in Asia to date except for Japan (Arbatli and others 2016).
  - Health care: classify reforms into three categories (Clements, Coady, and Gupta 2012):
    - macro-level controls to cap spending (regulate price and quantity of health services),
    - micro-level reforms to improve spending efficiency (promote generic drugs and preventative care),
    - demand-side reforms to curb demand (higher patient copayments and premium contributions).

Table excerpt (characteristics of Asian public pension systems, end of 2015):
- Position in demographic transition and predominant pension system type (main pension system covering the majority of workers):
  - Early dividend, defined benefit: Philippines
  - Early dividend, defined contribution: Indonesia
  - Early dividend, mixed: India
  - Late dividend, defined benefit: New Zealand, Vietnam
  - Late dividend, defined contribution: Malaysia, Singapore, Hong Kong SAR
  - Late dividend, mixed: Australia
  - Post dividend, defined benefit: Japan, Korea, Thailand
  - Post dividend, defined contribution: Hong Kong SAR (listed under late dividend in table), and China listed as mixed

(Note: The table describes the main pension system in each economy; some economies have smaller pension systems such as civil service pensions, social pensions, or minimum pension guarantees.)

*This box was prepared by Jacqueline Pia Rothfels.*

### Annex 2.1 — Data and methodology: estimating demographic impacts on growth and financial markets
- Demographics and labor supply:
  - Aggregate labor force projection formula (based on United Nations World Population Prospects, the 2015 Revision, median-variant scenario):
    L_t = Σ_{j=1}^{J} N_{t}^{j} LFP_{t}^{j} E_{t}^{j} w_{t}^{j}
    where j indicates the age-gender cohort, t indicates the year, N is number of individuals in each cohort, LFP and E denote cohort-specific labor force participation and employment rates, and w is a weight factor adjusting for difference between number of employees and effective units of labor supplied.
- Demographics and labor productivity:
  - Methodology follows Aiyar, Ebeke, and Shao (2017) and Feyrer (2007).
  - Baseline panel model (decade and country fixed effects):
    Δ log YW_it = α1 w55_it + α2 DR_it + u_i + η_t + ε_it
    where YW = real output per worker, w55 = share of workforce aged 55–64 years, DR = dependency ratio; instruments used include lagged birth rates 10, 20, 30, and 40 years ago to address endogeneity.
  - Data sample: 1950–2014, includes 12 Asian economies (Australia, China, Hong Kong SAR, India, Indonesia, Japan, Korea, Malaysia, New Zealand, the Philippines, Singapore, and Thailand) and more than 20 EU economies. Workforce and population data from UN and OECD; output per worker from Penn World Table 9.0.
  - Result (combined Asian and European sample): a 1 percentage point increase in the 55–64 age cohort of the labor force is associated with a reduction in total factor productivity of 0.74 of a percentage point (Annex Table 2.1.1).
- Demographics and capital flows:
  - EBA current account norm estimated over 1986–2013 using model CA = CA(X_S, X_I, X_CA, X_CF, Z, ΔR).
  - Policy variables P (fiscal balances, capital controls, social spending, reserve accumulation, financial policies proxied by private credit) can be set to desirable values P* to compute EBA CA norm and decompose actual CA deviations into policy gaps.
  - Demographic regressors: population growth, old-age dependency ratio (population over 64 divided by population 30–64), aging speed (projected change in old-age dependency ratio 20 years out), relative measures (relative to GDP-weighted sample averages). Projections based on UN World Population Prospects (2015 Revision, medium-variant scenario).
- Demographics and financial markets:
  - Baseline panel regression for real 10-year interest rates (r), year-over-year percent change in real stock returns (sr), and year-over-year percent change in real property prices (pp):
    r_it / sr_it / pp_it = b0 + b1 YD_it + b2 (YD_it × CO_it) + b3 OD_it + b4 (OD_it × CO_it) + b5 AS_it + b6 (AS_it × CO_it) + b7 RW_t + Controls_it + ε_it
    where YD = youth dependency ratio (population under 30 / population 30–64), OD = old-age dependency ratio (population over 64 / population 30–64), AS = aging speed, CO = capital openness index, RW = world interest rate; controls include GDP per capita relative to the United States, growth in labor productivity, and cyclically adjusted primary balance for the interest rate model; productivity growth only for stock and property models.
  - Data sample spans 1985–2013; interest rates model captures 42 economies globally (list of countries omitted here per content-generation rules).

### Key quantitative findings and statistics (preserve original figures)
- Japanese labor force reduction: over 7 percent between 1997 and 2016.
- Estimated negative impact on annual average growth from labor force decline: about 0.3 of a percentage point.
- Liu and Westelius (2016) productivity estimates:
  - 1 percentage point shift from age 30 to age 40 → total factor productivity up by about 4.4 percent.
  - 1 percentage point shift from age 40 to age 50 → total factor productivity down by 1.3 percent.
- Japan labor force participation rate changes (2011–2016):
  - Women: from 63 to 65 percent.
  - Ages 65–69: from 37 to 39 percent.
- Inflation sensitivity to aging in Japan (Liu and Westelius 2016): 1 percentage point increase in the old-age dependency ratio reduces inflation by about 0.1 of a percentage point.
- Projected age-related public expenditure erosion: up to 10 percentage points of GDP by 2050 under current policies.
- Projected public pension increases by 2050:
  - More than 5 percentage points of GDP in China, Korea, New Zealand, Thailand, and Vietnam (late- or post-dividend, defined benefit systems), absent policy measures.
  - Broadly unchanged in India, Indonesia, and the Philippines (early-dividend countries).
- Projected public health care expenditure increases by 2050:
  - More than 3 percentage points of GDP in post-dividend countries with generous systems (Korea and Japan), absent reforms.
- Japan health care reform potential fiscal savings: 2 percent of GDP by 2030 (Nozaki, Kashiwase, and Saito 2014).
- Demographics–TFP panel regression (Annex Table 2.1.1) result:
  - Workforce share aged 55–64 coefficient on change in real output per worker: −0.612*** (t-statistic −5.309).
  - Dependency ratio coefficient on change in real output per worker: −0.122 (t-statistic −0.695).
  - Sample observations: 571; Number of countries: 33.

_International Monetary Fund | April 2017_

### Annex Figure 2.1.1. Old-Age Dependency Relative to

### Annex Figure 2.1.1. Old-Age Dependency Relative to World Average

### Definition and Data Sources
- Old-age dependency is defined as the ratio of the population ages 65 and over divided by the population between 30 and 64 years old, in line with the External Balance Approach model.
- World average is calculated on a GDP-weighted basis.
- Sources: United Nations, World Population Prospects: 2015 Revision (medium-fertility scenario); IMF World Economic Outlook; and IMF staff projections.

### Key Regression Coefficients (Annex Table 2.1.3)
- Dependent variables covered: 10-Year Real Interest Rate; Percent Growth in Stock Return; Percent Growth in Real Property Price.
- Coefficients (standard errors in parentheses). Significance levels: ***p < 0.01, **p < 0.05, *p < 0.1.
  - Youth dependency Ratio
    - 10-Year Real Interest Rate: 9.41*** (2.46)
    - Percent Growth in stock Return: 67.28*** (23.66)
    - Percent Growth in Real Property Price: −11.32*** (3.96)
  - Youth dependency Ratio 3 Capital Openness
    - 10-Year Real Interest Rate: −7.96*** (1.96)
    - Percent Growth in stock Return: −231.01** (14.22)
    - Percent Growth in Real Property Price: 0.67 (4.00)
  - Old-age dependency Ratio
    - 10-Year Real Interest Rate: −18.3*** (6.28)
    - Percent Growth in stock Return: −232.69 (82.26)
    - Percent Growth in Real Property Price: 253.18* (31.77)
  - Old-age dependency Ratio 3 Capital Openness
    - 10-Year Real Interest Rate: 17.04*** (5.77)
    - Percent Growth in stock Return: 138.26* (75.02)
    - Percent Growth in Real Property Price: 25.37 (26.99)
  - Aging speed
    - 10-Year Real Interest Rate: −29.7*** (11.06)
    - Percent Growth in stock Return: 15.31* (163.18)
    - Percent Growth in Real Property Price: −100.95*** (34.05)
  - Aging speed 3 Capital Openness
    - 10-Year Real Interest Rate: 5.89** (10.09)
    - Percent Growth in stock Return: −317.04** (142.92)
    - Percent Growth in Real Property Price: 60.79* (31.86)
  - world Interest Rate
    - 10-Year Real Interest Rate: 0.65*** (0.16)
    - Percent Growth in stock Return: −1.18 (2.17)
    - Percent Growth in Real Property Price: 1.48*** (0.53)
  - Growth in Labor Productivity
    - 10-Year Real Interest Rate: 0.07 (0.06)
    - Percent Growth in stock Return: 4.75*** (0.98)
    - Percent Growth in Real Property Price: 0.30 (0.20)
  - Ratio of GDP per Capita to that of the US
    - Percent Growth in Real Property Price: 2.38* (1.43)
  - Cyclically Adjusted Primary balance
    - Percent Growth in Real Property Price: −0.00 (0.04)
- Observations: 740 (10-Year Real Interest Rate), 406 (stock Return), 716 (Real Property Price).
- Number of Groups: 42 (10-Year Real Interest Rate), 45 (stock Return), 56 (Real Property Price).

### Interaction Specification and Long-Term Interest Rates (Annex Table 2.1.5)
- Alternative specification uses interactions of dependency measures with (1 − Capital Openness).
- Key coefficients for 10-year real interest rate (standard errors in parentheses):
  - Youth dependency Ratio 3 (1 − Capital Openness): 8.26*** (1.95)
  - Old-Age dependency Ratio 3 (1 − Capital Openness): −16.16*** (5.51)
  - Aging speed 3 Capital Openness: −29.26*** (9.87)
  - world Interest Rate: 0.84*** (0.11)
  - Ratio of GDP per Capita to that of the US: 2.43* (1.39)
  - Cyclically Adjusted Primary balance: 0.00 (0.04)
  - Growth in Labor Productivity: 0.07 (0.06)
- Observations: 740. Number of Groups: 42.

### Long-Horizon Evidence (Annex Table 2.1.7)
- Results using Annual Model, 3-Year Averages, and 5-Year Averages for real rates are broadly similar to baseline.
- Selected coefficients (Annual / 3-Year / 5-Year; standard errors in parentheses):
  - Youth dependency Ratio: 9.41*** (2.46) / 9.68*** (3.62) / 9.33** (3.98)
  - Youth dependency Ratio 3 Capital Openness: −7.96*** (1.96) / −8.14*** (2.78) / −7.20** (2.78)
  - Old-Age dependency Ratio: −18.30*** (6.28) / −21.10** (9.60) / −17.00 (13.03)
  - Old-Age dependency Ratio 3 Capital Openness: 17.04*** (5.77) / 19.21** (8.56) / 18.53* (9.47)
  - Aging speed: −29.69*** (11.06) / −25.56*** (17.40) / −35.48* (20.57)
  - Aging speed 3 Capital Openness: 5.89** (10.09) / −20.69 (15.67) / 28.46* (17.07)
  - world Interest Rate: 0.65*** (0.16) / 0.61** (0.24) / 0.46 (0.52)
- Observations: Annual Model 740; 3-Year Averages 271; 5-Year Averages 166. Number of Groups: 42 for all.

### F Tests on Interaction Restrictions (Annex Table 2.1.4)
- Tests of null hypotheses that demographic coefficients equal zero when interacted with Capital Openness:
  - (1) Youth dependency Ratio 1 Youth dependency Ratio 3 Capital Openness = 0
    - f (1, 688) = 0.65; Prob . f = 0.4221
  - (2) Old dependency Ratio 1 Old dependency Ratio 3 Capital Openness = 0
    - f (1, 688) = 0.12; Prob . f = 0.7276
  - (3) Aging speed 1 Aging speed 3 Capital Openness = 0
    - f (1, 688) = 1.69; Prob . f = 0.1935
- IMF staff estimates indicate these null hypotheses cannot be rejected, supporting the alternative specification.

### Robustness and Unit-Root Testing (Annex Table 2.1.6)
- Concern: Demographic variables evolve slowly and may contain unit roots, risking spurious regressions.
- Unit-root test results (selected findings; figures in parentheses are p-values for the test under the null hypothesis of nonstationarity):
  - Real Interest Rate
    - Fisher (modified inverse chi square test) Constant: 3.23 (0.00) → I(0)
    - Im, Pesaran, Shin (t-value) Constant: 4.77 (0.00)
    - Dickey Fuller: −2.34 (0.09)
    - Result: I(0)
  - Youth Dependency
    - Fisher Constant: 15.27 (0.00) → I(0)
    - Im, Pesaran, Shin Constant: 64.74 (0.00)
    - Dickey Fuller: 4.32 (0.00)
    - Result: I(0)
  - Old Dependency
    - Fisher Constant: 5.90 (0.00)
    - Im, Pesaran, Shin Constant: 24.54 (1.00)
    - Dickey Fuller: 4.32 (1.00)
    - Result: I(1)
  - Aging Speed
    - Fisher Constant: 16.58 (0.00)
    - Im, Pesaran, Shin Constant: 22.99 (0.99)
    - Dickey Fuller: 21.87 (0.03)
    - Result: I(1)
  - World Interest Rate
    - Fisher Constant: (blank) 26.00 (1.00)
    - Im, Pesaran, Shin Constant: 25.95 (1.00)
    - Dickey Fuller: 10.61 (1.00)
    - Result: I(1)
  - Residuals (from baseline equation)
    - Fisher: 17.80 (0.00)
    - Im, Pesaran, Shin: 14.82 (0.00)
    - Dickey Fuller: −27.14 (0.00)
    - Result: I(0)
- Conclusion: Residual-based tests (Fisher and Im, Pesaran and Shin) reject the null hypothesis of unit root in residuals, reducing concern of misspecification from unit roots.

### Natural Interest Rate: Methodology and Results
- Methodology:
  - Natural rate estimated using a time varying parameter VAR (TVP-VAR) for three variables: growth rate of real GDP, inflation rate, and a measure of real interest rate.
  - Natural interest rate extracted using Wicksell’s definition as the rate for stable price equilibrium; a long-horizon (5-year forecast) of the observed real rate is used as measure.
- Data sample: 1970:Q1 – 2016:Q4, varying by country; Real GDP, CPI inflation, and policy rates from Haver Analytics.
- Results:
  - Real natural interest rates have fallen significantly in the United States and some other advanced Asian economies, such as Japan, Korea, and Australia.
  - Natural rates in emerging market economies, such as China, Malaysia, and Indonesia, are relatively stable.

### Aggregate Interpretation and Comparative Findings
- Combining regressions suggests the impacts of youth and old-age dependency ratios and aging speed on asset returns and interest rates tend to diminish as an economy becomes more open; under perfect openness these impacts become almost zero (Annex Table 2.1.5).
- On long-term interest rates and stock returns, impacts of domestic demographic factors tend to diminish with greater capital openness. On property prices, the effect of capital openness is small and often insignificant, reflecting local market characteristics.
- Multi-period (3-year and 5-year non-overlapping) returns emphasize low-frequency variation and produce results similar to the baseline annual specification.

*Source: IMF staff estimates and analyses as presented in Annex Figure 2.1.1 and accompanying annex tables.*

### 2.  AsIA: AT RIsK Of GROwING OLd bEfORE bECOMING RICh?

### 2.  AsIA: AT RIsK Of GROwING OLd bEfORE bECOMING RICh?

### Introduction and Main Findings
- Nearly 10 years after the global financial crisis, the prospect of mediocre future growth remains a concern, driven in part by a recent slowdown in productivity growth in many advanced economies and weakness in business investment.
- Asia has also experienced a productivity growth slowdown since the global financial crisis.
  - The slowdown has been most severe in the advanced economies of the region and in China.
  - The drivers in these economies appear similar to those in other advanced economies: less favorable demographics and a smaller impetus from trade integration.
  - In other emerging market economies and some developing economies in the region, the decline in productivity growth since the global financial crisis has been small.
- Reasons to place reforms to strengthen domestic sources of productivity growth high on the policy agenda in Asia:
  - External factors seem less likely to contribute as much to productivity growth going forward as they have in the past.
  - Demographics will increasingly weigh on productivity growth in a number of economies.
  - The sectoral shift toward services poses a challenge because productivity growth in services has been substantially lower than in manufacturing (Baumol, Blackman, and Wolff 1985).
- Positive features to build on:
  - R&D activity in the advanced economies of the region remains strong.
  - Emerging market and developing economies can capitalize on increased FDI and recent achievements in education, infrastructure spending, and private domestic investment.
  - Renewed trade liberalization and integration would benefit productivity.

*Prepared by Dirk Muir (lead author), Sergei Dodzin, Xinhao Han, Dongyeol Lee, and Ryota Nakatani, under the guidance of Thomas Helbling.*

### The Productivity Picture in Asia and the Pacific
- Two productivity concepts considered:
  - Total factor productivity (TFP): indicates output gains from a given set of factors (capital and labor).
  - Labor productivity: output per worker or per hour worked; rises with TFP and with capital deepening.
- Two assessment approaches:
  - Against past performance.
  - Relative to the technological frontier (United States used as the frontier reference in this chapter).
- Key observations from regional aggregates (averages over four periods to abstract from cyclical fluctuations):
  - Economic growth in Asia has generally held up well since the global financial crisis, compared with the precrisis period (2001–07) and with other advanced economies.
  - The difference between real GDP and TFP growth suggests postcrisis growth has been relatively more extensive (driven more by factor accumulation than by TFP improvements).

### Aggregate Total Factor Productivity (TFP) — group and country patterns
- Asia-Pacific advanced economies (Australia, Japan, Korea, Hong Kong SAR, New Zealand, and Singapore):
  - Growth was about 1 percentage point lower on average after the global financial crisis.
  - The decline in TFP growth after the global financial crisis is broadly comparable to that in other advanced economies.
- China and India:
  - The decline in average growth since the global financial crisis has been smaller; average growth is close to 8 percent.
  - China’s TFP decline is more substantial than that of its real GDP; India’s TFP reflects the decline less sharply.
- ASEAN-4 (Indonesia, Malaysia, the Philippines, and Thailand):
  - Real GDP and TFP growth after the global financial crisis remained relatively close to precrisis growth, with only a minor decline in both.
- Other Asia-Pacific emerging market and developing economies:
  - Growth remained high and stable, with only a minor reduction after the global financial crisis; TFP data are not available for all countries in the group, but some show TFP patterns similar to real GDP growth.
- Temporal considerations:
  - The presented data end in 2014.
  - TFP growth tends to be strongly procyclical; because real GDP growth broadly held up in 2015–16 compared to 2008–14, TFP trends for 2008–14 are likely broadly representative for the more recent period.
- Convergence:
  - TFP growth has not been high enough everywhere for strong convergence in TFP levels.
  - Relative indices (Penn World Tables) against the United States suggest relatively weak TFP convergence in China and India and in the ASEAN-4.
  - Asia-Pacific advanced economies have lost some ground against the United States, similar to other advanced economies.

### Productivity Developments by Sector (labor productivity focus)
- Sectoral analysis uses labor productivity due to data availability; labor productivity is complementary to TFP but not directly comparable in magnitude.
- Cross-country sectoral patterns:
  - Labor productivity growth in services has been much lower than in manufacturing for Japan, Korea, and the United States.
  - In Korea, services labor productivity growth improved since the global financial crisis; in Japan, it remained weak.
  - In Korea, manufacturing labor productivity growth has been broadly similar to or stronger than in the United States; manufacturing productivity in both Korea and Japan declined after the global financial crisis.
  - In ICT sectors, labor productivity growth in Korea and Japan has been relatively weak compared to the United States; since ICT sectors are likely important drivers of economy-wide labor productivity gains, this lag is a concern.
  - Productivity convergence in services stalled in Korea and some earlier gains reversed in Japan.
- Sector contributions decomposition (within-sector productivity growth and structural change effects) are presented for the United States, Japan, Korea, and selected Asian economies:
  - Manufacturing is typically an engine of labor productivity growth.
  - Services sectors, including finance, real estate, business services, public administration, health, education, trade and food, utilities and construction, transport, and information and communication, display varied contributions across countries and periods.
  - Agriculture, forestry, and fishing and mining and quarrying have country- and period-specific roles in total labor productivity growth.

### Implications and Policy Priorities (as emphasized in the chapter)
- Strengthen domestic sources of productivity growth through:
  - Improving effectiveness of R&D spending, especially in advanced economies of the region where R&D activity remains strong.
  - Capitalizing on favorable external factors (such as increased FDI) in emerging market and developing economies.
  - Enhancing records on educational achievements, infrastructure spending, and private domestic investment where mixed performance exists.
  - Promoting trade liberalization and integration to rebuild an external impetus to productivity growth.
- Address demographic headwinds and the sectoral shift toward services with policies that:
  - Mitigate the negative productivity impact of aging populations.
  - Promote productivity growth in services, including ICT and other service subsectors, to narrow the productivity gap with manufacturing and the frontier.

*International Monetary Fund | April 2017*

### 4. China

### 4. China

### Productivity contributions and sectoral patterns (2004–07 versus 2008–14)
- Results from a shift-share analysis decompose real labor productivity growth into “within” and “structural change” effects for 2004–07 and 2008–14.
- Manufacturing sectors accounted for about half of aggregate labor productivity growth generally, but "less in China, with a broader spread across sectors."
- A slowdown in manufacturing was an important reason for the overall productivity slowdown following the global financial crisis, although labor productivity also slowed in other sectors, including financial services.
- Finance, real estate, and business services accounted for between one-fifth and one-third of aggregate labor productivity growth, but labor productivity growth in these services sectors slowed after the global financial crisis; these sectors also accounted for most of the structural change effects in aggregate labor productivity growth.
- In China and India, part of labor productivity gains was generated by continuing reallocation from agriculture to other sectors.

### Domestic and external drivers of productivity: empirical findings
- The chapter assesses three primary concepts relevant for spillovers and productivity: (1) measures of R&D investment (domestic), and (2–3) international factors (international trade and FDI).
- A panel regression on labor productivity growth in 24 sectors across 19 advanced economies (sample period 1995–2007) relates productivity growth to the productivity gap, changes in the capital-labor ratio, and five explanatory variables: (1) R&D expenditure, (2) exports, (3) imports, (4) inward FDI, and (5) outward FDI. All variables are scaled by sectoral value added or gross output.
- Key regression results:
  - Labor productivity grows faster in industries with larger labor productivity gaps (catch-up growth); the relationship is statistically significant.
  - Higher R&D spending raises labor productivity. The impact of R&D spending is greater in sectors where labor productivity levels are already close to U.S. levels.
  - No substantial differences were found between manufacturing and services sectors in the magnitude of the productivity impact of R&D in the sample, though R&D spending has been small in services relative to manufacturing.
  - Higher trade openness has a positive and significant impact on labor productivity growth. The results suggest a larger positive impact if import openness increases by 1 percentage point than if export openness increases by 1 percentage point; imports of intermediate inputs are an important channel.
  - Inward FDI shows a statistically significant positive impact on labor productivity growth; outward FDI has a negative impact in the regressions.
- A thought experiment using the estimated coefficients asks what would happen to labor productivity growth if R&D, imports, exports, and inward FDI increased from the low end (25th percentile) to the high end (75th percentile) of the sample. The exercise suggests policies aimed at increased trade integration, greater import competition, and inward FDI would generate substantial productivity increases. The exercise also notes caveats: potential reverse causality, omitted variable bias, and that country-industry fixed effects capture many domestic factors.

### Broader country-level evidence (1980–2014)
- Country-level panel regressions of TFP over 1980–2014 across a broad set of Asia-Pacific countries indicate:
  - Domestic factors (such as R&D) generally have less impact than external factors (such as FDI) on TFP, though there is some evidence that the sources of TFP growth have shifted in favor of domestic factors (including financial development and absorptive capacity) since the global financial crisis.
  - This shift toward domestic factors will be key if advanced economies continue to slow and provide a weaker impetus to Asia-Pacific productivity.

### Research & Development investment in China
- Overall R&D spending increased notably among Asian countries since the global financial crisis, converging toward United States and other advanced economy levels; Korea has become a leader in R&D spending.
- As of 2014, after more than a decade of sustained increases, China was "at par with the average R&D spending in the European Union and with spending in Singapore."
- Data on patent applications filed by residents in their own country (absolute numbers and per unit of GDP) corroborate the R&D picture: "The strong increases in the number of patents in China and Korea stand out."
- The increase in R&D spending since the global financial crisis in some Asian economies would, all else being equal, imply that productivity growth should have increased noticeably; the fact that it did not suggests either:
  - Other factors more than offset the beneficial impact of increased R&D, or
  - Increased spending has not yet fully translated into marketable innovation and productivity gains because of problems of effectiveness.
- Much R&D spending in Asia is undertaken by large companies, especially multinational ones; the diffusion from R&D by leading firms might have slowed.
- The closing of the gap with, or surpassing, the United States in R&D spending in a growing number of Asian economies primarily reflects developments in manufacturing sectors, rather than services. In services, R&D spending in those economies is still lagging, which could plausibly help explain relatively lower productivity growth in services.

*Source: IMF staff calculations and analysis from AREO chapter "4. China" (excerpt). *

### 3. ThE “NEw MEdIOCRE” ANd ThE OUTLOOK fOR PROdUCTIvITy IN AsIA

### 3. ThE “NEw MEdIOCRE” ANd ThE OUTLOOK fOR PROdUCTIvITy IN AsIA

### Fixed Investment
- Fixed investment contributes to productivity via increased capital intensity and through new technologies embodied in new capital.  
- There is a possible measurement bias toward capital that may make the embodied-technology channel more important (see Box 3.1).  
- A downshift in the investment path—say, relative to pre-global-financial-crisis trends—would lower TFP.  
- After the global financial crisis, the rate of fixed investment (as a percent of the stock of physical capital) slowed in Asia-Pacific advanced economies to rates broadly at par with other advanced economies.  
- Estimates by Adler and others (2017) suggest such declines in investment rates could explain a sizable reduction in TFP, on the order of ¼ to ½ of a percentage point.  
- In the ASEAN-4, investment rates were broadly unchanged before and after the global financial crisis.  
- In several economies in the region, investment rates increased and supported productivity, including China and India and other emerging market and developing economies.  
- Prospects: fixed investment is expected to remain relatively weak for some time in economies where investment rates slowed after the global financial crisis; in China, rebalancing toward consumption implies investment rates are likely to slow, which, absent offsets, could weigh on productivity.

### International Trade
- International trade is an important channel of technology transfer.  
- Overall, trade openness (exports and imports) has generally moved sideways or declined since the global financial crisis; trade is therefore unlikely to have supported productivity.  
- Prospects: continued moderate trade growth with little change in export or import ratios; a trade-related boost to productivity overall seems unlikely (Constantinescu, Mattoo, and Ruta 2016).  
- Exceptions:
  - Trade openness increased after the global financial crisis in Asia-Pacific advanced economies and in other emerging market and developing economies in the region.  
  - The increase is particularly prominent in intra-Asia-Pacific trade and partly reflects further outsourcing of manufacturing from advanced economies to emerging market and developing economies in the region and the continued building/lengthening of supply chains between these economies.  
- Possible internal intensification of supply chains within China or India could have generated productivity improvements, but other factors may have offset such gains.

### Foreign Direct Investment
- FDI can be an engine of productivity growth; effects depend on inward versus outward FDI.  
- As a percent of GDP, FDI inflows increased in China, India, and the ASEAN-4 after the global financial crisis.  
- In Japan and Korea, FDI inflows remained broadly stable, while both registered noticeable increases in FDI outflows; China also saw some increase in FDI outflows.  
- Implication: FDI likely contributed to productivity increases mainly in emerging and developing Asia-Pacific economies after the global financial crisis.  
- FDI inflows into many emerging market and developing economies in the region are expected to remain strong, which should support further productivity increases.  
- Risks: increased protectionism could slow or reverse supply-chain building and offshoring.  
- Empirical analysis suggests FDI supports domestic fixed investment within Asia as a whole, another channel for raising productivity; the role of FDI has become increasingly important over time, particularly since the global financial crisis.

### Absorptive Capacity
- Absorptive capacity enables domestic economies to absorb positive influences from R&D and technology transfer; human capital is a key component.  
- The share of tertiary-enrollment in the relevant cohort has broadly increased across Asian economies over past decades; where initial tertiary enrollment was high (advanced economies), the rate of increase slowed since the global financial crisis compared to the precrisis boom of the early to mid-2000s.  
- The slowdown in building human capital is identified as one contributing factor to the productivity slowdown in advanced economies (Adler and others 2017).  
- In other countries, tertiary education shares increased rapidly after the global financial crisis; example: China’s tertiary enrollment share doubled between 2008 and 2014.  
- Public infrastructure (public capital stocks) is another dimension of absorptive capacity:
  - Public capital stocks are high in most Asia-Pacific advanced economies and China compared to other advanced economies and the United States; initial conditions thus seem favorable.  
  - In China and the ASEAN-4, the public-capital per capita ratio accelerated after the global financial crisis, reflecting increasing investment shares.  
- Research cited: Bom and Ligthart (2014) on output effects of related investment; IMF (2014) on benefits to firms and workers.

### Summary of Recent Drivers of the Slowdown
- Factors explaining the post-global-financial-crisis slowdown in productivity growth across many Asia-Pacific economies include:
  - Lower investment rates in some economies.  
  - Less impetus from international trade integration (broadly unchanged or declining trade openness).  
  - Slowing growth in human capital formation.  
  - Resource reallocation to less productive sectors and sectoral distortions (e.g., overcapacity).  
  - Demographics (aging) increasingly weighing on productivity prospects.  
- Contrasts:
  - Emerging market and developing economies in the region have generally seen many of these forces continue to contribute to productivity growth.

### Conclusions and Policy Implications
- The chapter finds that Asia experienced a productivity growth slowdown after the global financial crisis and little, if any, convergence to the technological frontier; productivity growth is likely to remain low for some time.  
- Policy priority: raising productivity growth should be a central economic policy priority in Asia.  
- Heterogeneity across countries implies different priorities:
  - Advanced Asia-Pacific economies:
    - Strengthen the effectiveness of R&D spending.  
    - Raise productivity in services sectors through increased competition to spur innovation and adaptation (see Box 3.2 for Australia and Singapore cases).  
  - China:
    - Improvements since the crisis include increased R&D spending and rapid educational attainment gains; however, trade openness has declined since earlier gains were absorbed, and resource misallocation and incentive distortions (e.g., sectoral overcapacity) are holding back productivity.  
  - India:
    - Key challenge: raise productivity in agriculture, which employs about half of Indian workers.  
    - Policies: address structural bottlenecks and enhance market efficiency—liberalize commodity markets, give farmers more flexibility in distribution and marketing to raise competitiveness, efficiency, and transparency in state agriculture markets.  
    - Input subsidies to farmers should be administered through direct cash transfers rather than underpricing of agricultural inputs, because such subsidies have had large negative impacts on agricultural output.  
  - Other emerging market and developing economies:
    - Capitalize on rises in FDI inflows by increasing related productivity spillovers via increases in absorptive capacity and domestic investment.  
    - Continue progress on human capital formation (Japan and Korea as leaders; ASEAN-4 following), including strengthening the quality and flexibility of domestic education systems.  
    - In some economies, expand public infrastructure to close noticeable gaps.

### Box: Biased Technical Change and Policy Implications
- Issue: automation in manufacturing and services has increased substitution away from labor toward automated processes; technical bias matters for productivity, factor compensation, and employment.  
- This box investigates bias in China, Japan, Korea (and the United States for comparison) and finds a bias toward capital equipment and high-skilled labor away from low-skilled labor in a number of industries.  
- Measurement framework: multi-factor cost approach (Binswanger 1974) using five input factors (capital goods, high-skilled labor, medium-skilled labor, low-skilled labor, intermediate goods) across four broad industries (agriculture; food, textiles, and leather; machinery and equipment; finance).  
- Bias measure for capital, B_K(t), approximated as:
  - B_K(t) ≈ (s_Kt11 2 s_Kt)/s_Kt given cost of capital p_K, wage w, and price of intermediate goods p_I.  
- Periods examined: 1995–96, 1997–2000, 2001–07, and 2008–09.  
- Findings:
  - General tendency toward a positive bias in capital goods and a negative bias against low-skilled labor in all countries considered.  
  - Capital bias is stronger in China (consistent with relative capital scarcity), though the bias is declining over time.  
  - Mild bias toward high-skilled labor in research-intensive and high-knowledge service industries (machinery and equipment; finance).  
  - Strong negative bias against low-skilled labor in the most technically advanced country (United States) and the least negative bias in China.  
  - In China, bias toward high-skilled labor is also observed in other industries, consistent with relative scarcity.  
- Implications:
  - Industries with a positive bias toward capital goods should generally show higher labor productivity; aggregate effects depend on where labor is reallocated and the economy’s ability to redeploy workers without increasing unemployment.  
  - Policymakers should combine productivity increases with inclusive growth strategies.  
  - The widespread negative bias toward low-skilled labor and positive bias toward high-skilled labor imply that increasing human capital and improving the economic environment can help mitigate economic effects from this transition.

*International Monetary Fund | April 2017*

### Box 3.1. Biased Technical Change and Productivity

### Box 3.1. Biased Technical Change and Productivity

### Summary of issue
- The box discusses the role of government in augmenting productivity growth in Asia, emphasizing government engagement with the private sector rather than industrial policy mandates.
- Productivity growth can be stimulated through macroeconomic and structural tax and expenditure policy, but the box focuses narrowly on government roles that facilitate private-sector-led productivity improvements.

### Three-pronged approach recommended for government engagement
- Providing infrastructure through public investment, or by facilitating private efforts.
- Putting in place a strong regulatory environment and secure legal framework in which to conduct business, have ownership, and engage smoothly with capital and labor.
- Establishing public institutions that can serve as public goods for the private sector and provide quality information.

### Rationale and limits
- The box clarifies this is not a call for direct industrial policy; private involvement is important and can be facilitated by governments acting as central coordinators for public goods.
- Some countries in the past have used industrial policy successfully, but to maintain productivity growth governments should avoid mandating productivity and instead focus on enabling environments and public goods.

### Case example: Australia (illustrative of the approach)
- Public institutions send signals to the private sector, provide comprehensive information, and validate private initiatives.
  - Infrastructure Australia: identifies infrastructure needs and evaluates plans from governments and the private sector.
  - Productivity Commission: provides analysis on the state of productivity growth and advice on legislation as an arm’s-length observer.
- Legislative work and direct spending supplement institutional activities.
  - Government conducts special studies (for example, the Competition Policy Review) to strengthen legal and regulatory frameworks and simplify doing business.
  - Active engagement in trade policy, including intellectual property protections under the now-defunct Trans-Pacific Partnership agreement.
- Public spending and targeted programs:
  - Government leads large-scale infrastructure projects while encouraging private participation.
  - The National Innovation and Science Agenda (NISA) uses modest budgets with ambitious aims to incubate industries (for example, information and communication technology), facilitate research and development and industry collaboration via:
    - increasing public spending on many smaller initiatives over five years;
    - addressing perceived gaps in critical science capabilities and access to quality private funding; and
    - simplifying business regulation and interaction with the public sector.
- The effectiveness of some recent initiatives (including NISA) is still to be evaluated.

### Replicability and variation across economies
- Australia’s model could be replicated in other Asia-Pacific economies by using limited government funds more efficiently and avoiding dependence on the public sector to mandate productivity growth.
- Some countries, such as Singapore, are adapting aspects of Australia’s approach but with a more active government role (see Box 3.2 for comparative case study material).

*International Monetary Fund | April 2017*

### Annex Table 3.2.2. Baseline Country-Level Total Factor Productivity Results

### Annex Table 3.2.2. Baseline Country-Level Total Factor Productivity Results

### Key empirical findings (by country group)
- Asia-Pacific:
  - R&D Stock: 0.005*** (0.001)
  - FDI Stock: 0.089*** (0.007)
  - Imports: 20.001*** (0.000)
  - Financial Development: 0.002*** (0.000)
  - Countries: 145
  - Observations: 454
  - R-squared: 0.93
- Asian AEs:
  - R&D Stock: 0.019*** (0.006)
  - FDI Stock: 0.067*** (0.024)
  - Imports: 0.001** (0.000)
  - Financial Development: 0.001 (0.001)
  - Countries: 93
  - Observations: 153
  - R-squared: 0.81
- Other A-PAEs:
  - R&D Stock: 0.005*** (0.001)
  - FDI Stock: 0.103*** (0.009)
  - Imports: 20.003*** (0.001)
  - Financial Development: 0.002*** (0.001)
  - Countries: 36
  - Observations: 330
  - R-squared: 0.90
- EMdEs:
  - R&D Stock: 0.008*** (0.003)
  - FDI Stock: 0.014*** (0.005)
  - Imports: 0.001*** (0.000)
  - Financial Development: 0.000** (0.000)
  - Countries: 70
  - Observations: 1,105
  - R-squared: 0.87
- market and developing economies (EMDEs):
  - R&D Stock: 0.001 (0.001)
  - FDI Stock: 0.046*** (0.006)
  - Imports: 20.002*** (0.000)
  - Financial Development: 0.001 (0.001)
  - Countries: 0 (table shows EMDEs column header but country count and some stats presented above)

### Statistical details
- White’s heteroscedasticity robust standard errors are in parentheses.
- Constants, country fixed effects, and year fixed effects are included but not reported.
- Significance notation: *p < .10; **p < .05; ***p < .01.
- Definitions in notes: AEs 5 advanced economies; A-P 5 Asia-Pacific; EMdEs 5 emerging market and developing economies; fdI 5 foreign direct investment; R&d 5 research and development.

*source: IMf staff calculations.*

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### Annex Table 3.2.3. Absorptive Capacity in Asia

### Key empirical findings (three specifications labeled Asia-Pacific)
- Specification 1:
  - R&D Stock: 0.012*** (0.004)
  - FDI Stock: 0.118*** (0.012)
  - Imports: 20.001* (0.001)
  - Financial Development: 0.001* (0.001)
  - Interaction of FDI Stock and Human Capital: 0.002** (0.001)
  - Interaction of FDI Stock and Public Capital: 20.011 (0.014)
  - Countries: 12
  - Observations: 203
  - R-squared: 0.95
- Specification 2:
  - R&D Stock: 0.005*** (0.001)
  - FDI Stock: 0.087*** (0.008)
  - Imports: 20.001*** (0.000)
  - Financial Development: 0.002*** (0.000)
  - Interaction of FDI Stock and Human Capital: 0.002** (0.001)
  - Interaction of FDI Stock and Public Capital: 20.099** (0.044)
  - Countries: 13
  - Observations: 430
  - R-squared: 0.93
- Specification 3:
  - R&D Stock: 0.023*** (0.005)
  - FDI Stock: 0.096*** (0.013)
  - Imports: 20.002** (0.001)
  - Financial Development: 0.002** (0.001)
  - Interaction of FDI Stock and Human Capital: 0.002** (0.001)
  - Countries: 11
  - Observations: 184
  - R-squared: 0.95

### Statistical details
- White’s heteroscedasticity robust standard errors are in parentheses.
- Constants, country fixed effects, and year fixed effects are included but not reported.
- Definitions in notes: AEs 5 advanced economies; EMEs 5 emerging market economies; fdI 5 foreign direct investment; R&d 5 research and development.
- Significance notation: *p < .10; **p < .05; ***p < .01.

*source: IMf staff calculations.*

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### Annex Table 3.2.4. Asia before and after the Global Financial Crisis

### Key empirical findings (periods 1980–2007 and 2008–14)
- 1980–2007:
  - R&D Stock: 0.010*** (0.003)
  - FDI Stock: 0.127*** (0.014)
  - Imports: 20.001 (0.001)
  - Financial Development: 0.002** (0.001)
  - Interaction of FDI Stock and Human Capital: 0.001 (0.001)
  - Countries: 12
  - Observations: 137
  - R-squared: 0.97
- 2008–14:
  - R&D Stock: 0.090*** (0.027)
  - FDI Stock: 0.107*** (0.027)
  - Imports: 20.003*** (0.001)
  - Financial Development: 0.001 (0.001)
  - Interaction of FDI Stock and Human Capital: 0.002** (0.001)
  - Countries: 11
  - Observations: 66
  - R-squared: 0.98

### Statistical details
- White’s heteroscedasticity robust standard errors are in parentheses.
- Constants, country fixed effects, and year fixed effects are included but not reported.
- Excludes Australia and New Zealand.
- Significance notation: *p < .10; **p < .05; ***p < .01.

*source: IMf staff calculations.*

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### Annex Table 3.2.5. Complementarity between Domestic Investment and Foreign Direct Investment in Emerging and Developing Asia and the Pacific

### Key empirical findings (five sample windows)
- 1978–2015:
  - Lagged Investment: 0.690*** (0.036)
  - Inward FDI Flows: 0.133** (0.060)
  - Lagged Real Growth: 0.156** (0.072)
  - Interest Rate: 0.038** (0.016)
  - Observations: 470
  - R-squared: 0.84
- 1992–2015:
  - Lagged Investment: 0.664*** (0.041)
  - Inward FDI Flows: 0.126* (0.065)
  - Lagged Real Growth: 0.107 (0.084)
  - Interest Rate: 0.036** (0.017)
  - Observations: 382
  - R-squared: 0.83
- 1997–2015:
  - Lagged Investment: 0.571*** (0.046)
  - Inward FDI Flows: 0.146** (0.069)
  - Lagged Real Growth: 0.129 (0.089)
  - Interest Rate: 0.194** (0.088)
  - Observations: 330
  - R-squared: 0.82
- 2001–15:
  - Lagged Investment: 0.557*** (0.055)
  - Inward FDI Flows: 0.170*** (0.077)
  - Lagged Real Growth: 0.111 (0.104)
  - Interest Rate: 20.046 (0.182)
  - Observations: 273
  - R-squared: 0.81
- 2008–15:
  - Lagged Investment: 0.325*** (0.078)
  - Inward FDI Flows: 0.566*** (0.122)
  - Lagged Real Growth: 0.144 (0.195)
  - Interest Rate: 20.507 (0.361)
  - Observations: 147
  - R-squared: 0.83

### Statistical details
- Standard errors are in parentheses.
- Constants, country fixed effects, and year fixed effects are included but not reported.
- Excludes Australia and New Zealand.
- fdI 5 foreign direct investment.
- Significance notation: *p < .10; **p < .05; ***p < .01.

*source: IMf staff calculations.*

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_Source: https://www.imf.org/-/media/files/publications/reo/apd/2017/areo0517.pdf_