## Introduction and Main Findings

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### Trends
- Asia is aging fast; the speed of aging is especially remarkable compared to the historical experience in Europe and the United States.
- Parts of Asia risk becoming old before becoming rich; the region’s per capita income relative to the United States stands at much lower levels than those reached by mature advanced economies in the past.
- Asia is shifting from being the biggest contributor to the global working-age population to subtracting hundreds of millions of people from it.
- Working-age population definition used: persons 15 to 64 years old (international definition).
- Youth dependency ratio: persons aged 14 and below as a share of the working-age population. Old-age dependency ratio: persons aged 65 and above as a share of the working-age population.
- Population projections based on United Nations, World Population Prospects: 2015 Revision (medium-fertility scenario with unchanged net migration flows).
- Key projected demographic magnitudes:
  - The population growth rate is projected to fall to zero for Asia by 2050.
  - 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.
- Demographic classification (2015 → 2030) of major Asian economies (selected):
  - Post dividend: China, Hong Kong SAR, Japan, Korea, Thailand (Singapore projected to move to post-dividend by 2030).
  - Late dividend: Australia, Malaysia, New Zealand, Singapore (2015), Vietnam.
  - Early dividend: India, Indonesia, Philippines (Indonesia projected to transition to late-dividend by 2030).
- Migration:
  - Immigration has been sizable in Australia, New Zealand, Hong Kong SAR, and Singapore, substantially slowing the decline of working-age populations there.
  - Net migration is relatively small for China, Japan, Korea, and most ASEAN members.
- Speed of aging example:
  - The number of years it took for the old-age dependency ratio to increase from 15 to 20 percent: 26 years in Europe, more than 50 years in the United States, but less than 10 years (or projected to be) for countries such as China, Japan, Korea, Thailand, Singapore, and Vietnam.
- Old-age dependency ratio example levels (selected snapshots):
  - Japan: 43.3 percent in 2015 → 71.0 percent in 2050.
  - Hong Kong SAR: 20.6 percent in 2015 → 64.6 percent in 2050.
  - Korea: 18.0 percent in 2015 → 65.8 percent in 2050.
  - China: 13.1 percent in 2015 → 46.7 percent in 2050.
  - India: 8.6 percent in 2015 → 20.5 percent in 2050.
  - Philippines: 7.2 percent in 2015 → 14.5 percent in 2050.

### Growth: historical and projected impacts
- Historical: Asia reaped a “demographic dividend” as the number of workers grew faster than the number of dependents.
- Projection: Rapid aging is set to create a demographic tax on growth in several countries.
- Estimated impacts (average annual GDP growth effects over the next three decades):
  - Post-dividend countries (China and Japan): demographics could subtract ½ to 1 percentage point from annual GDP growth.
  - Early-dividend countries (India and Indonesia): demographics could add 1 percentage point to annual GDP growth if the transition is well managed.
  - Overall for Asia: demographics are likely to be slightly negative for Asian growth.
  - Global effect: demographics could subtract 0.1 of a percentage point from annual global growth over the next three decades (or 0.2 of a percentage point if early-dividend countries are unable to reap the demographic dividend).
- Migration role: In Australia, Hong Kong SAR, New Zealand, and Singapore, immigration—if past trends continue—could soften the impact of aging or prolong the demographic dividend.
- Methodology and baseline assumptions for growth accounting:
  - 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.
  - Baseline compares UN medium-fertility scenario (which includes migration) to a hypothetical status quo with constant population size and age structure; UN zero-migration scenario is considered separately.
- Baseline growth-impact examples (average, 2020–50 relative to status quo):
  - Japan: impact could reduce the average annual growth rate by almost 1 percentage point.
  - China: substantial negative impact; China is highlighted as the largest absolute decline in working-age population: decline of 170 million over next 35 years.
- Sensitivity to fertility assumptions:
  - Compared to the UN’s medium-fertility scenario, the average annual growth rate is about 0.2 percentage point higher in the UN’s high-fertility scenario and about 0.2 percentage point lower in the low-fertility scenario.

### Per capita and sectoral perspectives
- Country ordering changes slightly on a per capita basis relative to aggregate growth impacts.
  - The demographic drag is smaller for Japan on a per capita basis, but larger for Hong Kong SAR and Singapore because the positive impact of immigration is partially eliminated in the per capita perspective.
- Sectoral and occupational differences:
  - Productivity-age profile varies by occupation: productivity of workers in physically demanding professions tends to decline with age, while productivity may increase with age in professions such as lawyers, managers, and doctors.
  - Low per capita income countries (e.g., Thailand, Vietnam) tend to have larger shares of workforce in occupations where productivity tends to decline with age, underscoring need for structural transformation.

### Aging and Total Factor Productivity (TFP)
- Workforce aging measure: share of workers 55–65 years old in total workforce projected to increase substantially by 2050 in most Asian countries, with largest increases in China, Malaysia, and Vietnam.
- Evidence on productivity and aging:
  - Several studies 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).
  - Acemoglu and Restrepo (2017) find no robust negative impact of aging on productivity.
- Estimated effect: an increase in the share of older workers is associated with a significant reduction in labor productivity growth.
- Decomposition: workforce aging is associated with lower annual TFP growth by 0.1 to 0.3 of a percentage point on average for Asia (see Annex 2.1).
- Estimated impact on GDP growth (average, 2020–50): 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).
- Quantitative regression result (Annex 2.1): 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).

### Labor Force Participation Rate (LFPR) scenarios
- Historical LFPR changes (1990–2015):
  - 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, notably Australia, New Zealand, and Singapore.
  - Japan: LFPR increased close to 6 percentage points since 1990—the largest increase in the region.
- Scenario: if other Asian economies achieved a gradual increase in LFPR for all age and gender groups by 6 percentage points (based on Japan’s 1990–2015 experience), the impact on annual GDP growth is 0.2 to 0.3 of a percentage point.
- Larger LFPR changes: 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.

### Investment and capital-to-effective-labor ratio
- Baseline assumption: constant capital-to-effective-labor ratio.
- Empirical findings: workforce aging is associated with higher capital per worker (accounting for TFP), but the economic effect is small; no statistically significant relationship found between old-age dependency ratio and capital per worker.
- Conclusion: constant capital-to-labor-ratio assumption is a reasonable approximation for thinking about the next three decades.

### Welfare implication of sustained lower growth
- A sustained 0.5 percentage point reduction in growth per year would reduce the level of GDP by 2050 by about 15 percent.

### Additional regional and historical context
- Between 1970 and 2010, Asia contributed more to the growth of the global working-age population than the rest of the world combined; this pattern is reversing as East Asian working-age populations decline.
- Absolute projected declines in working-age population (examples):
  - China: decline of 170 million in the working-age population over the next 35 years.
  - Substantial declines also projected for Japan, Korea, and Thailand.
- Contrast with other regions: April 2015 REO Sub-Saharan Africa projected that Africa will account for most of the growth in the global working-age population in coming decades.

### Baseline country examples (average, 2020–50)
- Post-dividend countries: demographic trends could reduce growth by ½ to 1 percentage point per year in absolute and per capita terms over the next three decades.
- Example time-path for China: the drag rises over time from 0.4 in the first decade to about 1.1 percentage points in the last decade.
- Immigration illustrative requirements to maintain dependency ratios by 2030:
  - Australia would need immigration equal to approximately 23 percent of the actual workforce.
  - Singapore would need approximately 51 percent.

### External flow balance and capital flows
- Diversity of demographic trends creates opportunities for capital flows and cross-border risk sharing: savings from surplus countries can finance capital needs in younger economies.
- IMF External Balance Approach (EBA) model projections:
  - Over the next decade, surpluses of some Asian economies are projected to increase due to demographics.
  - The impact is material only for a small set of countries.
  - Overall effect on global imbalances is likely to be limited: about 0.1 of a percentage point of global GDP over the next decade.
- EBA directional effects (expected):
  - Population growth: savings ↓, investment ↑, current account ↓.
  - Old-age dependency: savings ↓, investment ↓, current account ambiguous.
  - Aging speed: savings ↑, investment ↓, current account ↑.
- By 2020–30 projections:
  - 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, Vietnam) will have very high speeds of aging until 2030; Australia and New Zealand will have lower speeds than the world average.
- Projected impact on current account norms (change from 2020 to 2030): demographics likely to exert upward pressure on current account balances in surplus countries (Japan, Korea, Thailand) given rising aging speeds; downward pressure among some deficit countries (notably New Zealand) given falling aging speed.
- Caveat: estimates are partial-equilibrium and hold other macro variables fixed; broader interactions (e.g., with fiscal balance, productivity, output gap) could change magnitudes.

### Financial markets: interest rates, stocks, and real estate
- Demographic trends likely to put downward pressure on real interest rates and asset returns for most major countries in Asia.
- For financially open countries, domestic demographic effects are likely to be less important; changes in the world interest rate—possibly driven by global aging—will likely matter more.
- Channels to interest rates:
  - Youth dependency: rising youth dependency increases interest rates; youth dependency expected to fall drastically in early-dividend countries, reducing interest rates.
  - Old-age dependency: rising old-age dependency tends to reduce savings and may reduce interest rates; theoretical impact is ambiguous.
  - Aging speed: higher aging speed tends to lower interest rates via higher life-cycle savings and lower current investment.
- Empirical magnitudes (Annex Table 2.1.5, closed-economy interpretation scaled by capital openness):
  - A 1 percentage point increase in youth dependency increases the interest rate by 8.26 basis points when the economy is fully closed, while there is no impact in the case of a fully open economy.
  - Old-Age dependency: 216.16 (standard error 5.51) — effect vanishes with full openness.
  - Aging speed: 229.26 (standard error 9.87) — effect vanishes with full openness.
- Projected impact on real interest rates (2020–2030):
  - Overall, demographic trends could put downward pressure on interest rates by about 1 to 2 percentage points in the next decade, all else being equal.
  - Effect depends on degree of openness, state of aging, and speed of aging.
  - For fully open countries, demographic factors do not have a direct effect on domestic long-term interest rates.
  - Post-dividend countries (Korea and Thailand): rising old-age dependency is expected to depress interest rates.
  - Early-dividend countries (India and the Philippines): falling youth dependency is projected to reduce interest rates.
- Stocks and real estate:
  - Empirical results: lower youth (or higher old-age) dependency is associated with lower stock returns (interest rate channel dominates), but results are not statistically strong.
  - Links between demographic variables and real estate prices are weak empirically.
  - Openness reduces the impact of domestic demographic factors on stock returns; openness plays an insignificant role for real estate.

### Japan: demographic headwinds — growth, inflation, and monetary policy (box example)
- Japan’s working-age population has been declining since 1997; overall population started to shrink only after 2010.
- The falling working-age population together with change in overall labor force participation 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 (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 developments:
  - Female LFPR rose from 63 to 65 percent between 2011 and 2016.
  - LFPR for workers ages 65 to 69 increased from 37 to 39 percent between 2011 and 2016.
- Demographics and inflation:
  - A 1 percentage point increase in the old-age dependency ratio reduces the inflation rate by about 0.1 of a percentage point (Liu and Westelius 2016).
- Monetary policy implications:
  - Structural excess savings and a low neutral rate of interest may render monetary policy unable to stimulate the economy, keeping inflation below target and raising the risk of secular stagnation.

### Fiscal implications of demographic trends
- Projected fiscal pressures:
  - 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, the increases would be driven by pensions.
- Public pensions projections:
  - Late- or post-dividend countries with defined benefit systems are likely to see larger increases.
  - For 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 percent of GDP) are expected to remain broadly unchanged.
- Health care projections:
  - 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.
  - Nozaki, Kashiwase, and Saito (2014) show that health care reforms in Japan could generate fiscal savings of 2 percent of GDP by 2030.
- Policy options:
  - Pensions: introduce automatic adjustment mechanisms linking retirement ages (or benefits) to life expectancy with adequate safety nets for the elderly poor.
  - Health care: macro-level controls, micro-level reforms to improve spending efficiency, and demand-side reforms (higher patient copayments and premium contributions).

### Retirement systems and financial sector responses
- 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 impact of entitlement reforms, and reduce incentives for precautionary savings.
- Reforming management of public pension funds:
  - Reducing home bias—along the lines of recent Government Pension Investment Fund reforms in Japan—could help raise investment returns.
- New financial products to lower precautionary savings:
  - Reverse mortgages and annuities to insure against longevity risks.
- Cross-border risk sharing and financial integration:
  - Savings in late- or post-dividend countries seeking higher returns could finance infrastructure gaps in early-dividend countries.
  - Increasing availability of “safe assets” (long-term government bonds or inflation-linked securities) can be attractive for pension funds and insurance companies.
- Financial integration in Asia remains low: 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.

### Policy implications and recommendations (priority actions)
- Urgent priorities:
  - Protect vulnerable elderly populations.
  - Prolong strong growth through early adaptation of macroeconomic policies before aging sets in.
- Macroeconomic policy actions:
  - Fiscal policy:
    - Introduce a credible medium-term fiscal framework to secure debt sustainability.
    - Shift the tax burden from labor to consumption.
    - Revamp the social safety net.
    - With a credible medium-term fiscal framework, fiscal policy can be used more actively in the short run given its higher potency in a low-interest-rate environment, including to support aging-related structural reforms.
  - Monetary policy:
    - Study how monetary transmission may change with aging (e.g., greater transmission through asset prices and household wealth rather than corporate borrowing costs).
    - Regular assessment of the neutral monetary stance is needed to avoid a potential tightening bias as the natural interest rate declines.
    - Prolonged low interest rates call for a strong macro-prudential framework to mitigate financial stability risks.
- Structural labor market reforms:
  - Raise labor force participation, especially for women and the elderly:
    - Expand child-care facilities, remove fiscal disincentives to dependents’ labor participation, 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.
    - Japan’s experience is highlighted as instructive.
  - Encourage foreign workers via targeted guest worker programs to address labor shortages (examples: Australia, Hong Kong SAR, New Zealand, Singapore).
  - Promote active labor market policies: improve affordable health care for mature workers; facilitate human capital upgrading and retraining.
- Structural pension reforms:
  - Strengthen pension systems given rapid aging, fiscal costs, and relatively low pension coverage.
  - Entitlement reform through automatic adjustment mechanisms that link changes in retirement age (or benefits) to life expectancy to de-politicize pension reform and contain pension costs.
- Retirement system financial-sector measures:
  - Reduce home bias in public pension fund portfolios.
  - Expand availability of long-term “safe assets.”
  - Develop financial products (annuities, reverse mortgages) to reduce precautionary savings.

### Annex and methodological notes (data and econometrics)
- Demographics and projections use United Nations World Population Prospects: 2015 Revision (median-variant scenario).
- Productivity regressions follow Aiyar, Ebeke, and Shao (2017) and Feyrer (2007); baseline model: Δ log YW_it = α1 w55_it + α2 DR_it + u_i + η_t + ε_it.
- Endogeneity addressed by instrumenting workforce share and dependency ratio with lagged birth rates 10, 20, 30, and 40 years ago.
- Data span 1950–2014; sample includes 12 Asian economies and more than 20 EU economies. Output per worker from Penn World Table 9.0.
- Panel regression key result (Annex Table 2.1.1): workforce share Aged 55–64 associated with negative and statistically significant coefficients across specifications; observations: 571; number of countries: 33.
- EBA current account norm estimated over 1986–2013 with demographic variables including population growth, old-age dependency ratio, and aging speed.
- Demographics and financial markets baseline panel regression:
  - Dependent variables: r (10-year real interest rates), sr (year-over-year percent change in real stock returns), pp (year-over-year percent change in real property prices).
  - Regressors include YD (youth dependency), OD (old-age dependency), AS (aging speed), interactions with capital openness index (CO), and the world interest rate (RW).
  - Data sample spans 1985–2013; interest rates model captures 42 economies.
- Key econometric findings (selected coefficients, Annex Tables):
  - Annual model coefficients for 10-Year Real Interest Rate: Youth dependency Ratio: 9.41*** (2.46); Old-age dependency Ratio: 218.3*** (6.28); Aging speed: 229.7*** (11.06); world Interest Rate: 0.65*** (0.16). Observations: 740; Number of Groups: 42.
  - Annex Table 2.1.5 (alternative specification): Youth dependency Ratio 3 (1 − Capital Openness): 8.26*** (1.95); Old-Age dependency Ratio 3 (1 − Capital Openness): 216.16*** (5.51); Aging speed 3 (1 − Capital Openness): 229.26*** (9.87); world Interest Rate: 0.84*** (0.11). Observations: 740; Number of Groups: 42.
- Stationarity and robustness:
  - Residuals from baseline regressions reject unit-root nulls; real interest rate is I(0); old dependency and aging speed are I(1) under some tests; long-horizon averages broadly consistent with annual estimates.

*Prepared by Serkan Arslanalp and Jaewoo Lee (lead authors), Minsuk Kim, Umang Rawat, Jacqueline Pia Rothfels, Jochen Markus Schmittmann, and Qianqian Zhang. Source: areo0517c2 (PDF chapter/section).*

### Introduction and Main Findings

### Introduction and Main Findings

### Trends
- Asia is aging fast; the speed of aging is especially remarkable compared to the historical experience in Europe and the United States.
- Parts of Asia risk becoming old before becoming rich; the region’s per capita income relative to the United States stands at much lower levels than those reached by mature advanced economies in the past.
- Asia is shifting from being the biggest contributor to the global working-age population to subtracting hundreds of millions of people from it.
- Working-age population definition used: persons 15 to 64 years old (international definition).
- Youth dependency ratio: persons aged 14 and below as a share of the working-age population. Old-age dependency ratio: persons aged 65 and above as a share of the working-age population.
- Population projections are based on United Nations, World Population Prospects: 2015 Revision (medium-fertility scenario with unchanged net migration flows).
- Key projected demographic magnitudes:
  - The population growth rate is projected to fall to zero for Asia by 2050.
  - 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.
- Demographic classification (2015 → 2030) of major Asian economies (selected):
  - Post dividend: China, Hong Kong SAR, Japan, Korea, Thailand (Singapore projected to move to post-dividend by 2030).
  - Late dividend: Australia, Malaysia, New Zealand, Singapore (2015), Vietnam.
  - Early dividend: India, Indonesia, Philippines (Indonesia projected to transition to late-dividend by 2030).
- Migration:
  - Immigration has been sizable in Australia, New Zealand, Hong Kong SAR, and Singapore, substantially slowing the decline of working-age populations there.
  - Net migration is relatively small for China, Japan, Korea, and most ASEAN members.
- Speed of aging example:
  - The number of years it took for the old-age dependency ratio to increase from 15 to 20 percent: 26 years in Europe, more than 50 years in the United States, but less than 10 years (or projected to be) for countries such as China, Japan, Korea, Thailand, Singapore, and Vietnam.
- Old-age dependency ratio example levels (selected country snapshots from Table 2.2):
  - Japan: 43.3 percent in 2015 → 71.0 percent in 2050.
  - Hong Kong SAR: 20.6 percent in 2015 → 64.6 percent in 2050.
  - Korea: 18.0 percent in 2015 → 65.8 percent in 2050.
  - China: 13.1 percent in 2015 → 46.7 percent in 2050.
  - India: 8.6 percent in 2015 → 20.5 percent in 2050.
  - Philippines: 7.2 percent in 2015 → 14.5 percent in 2050.

### Growth
- Historical: Asia reaped a “demographic dividend” as the number of workers grew faster than the number of dependents.
- Projection: Rapid aging is set to create a demographic tax on growth in several countries.
- Estimated impacts (average annual GDP growth effects over the next three decades, per chapter findings):
  - Post-dividend countries such as China and Japan: demographic trends could subtract ½ to 1 percentage point from annual GDP growth.
  - Early-dividend countries such as India and Indonesia: demographics could add 1 percentage point to annual GDP growth if the transition is well managed.
  - Overall for Asia: demographics are likely to be slightly negative for Asian growth.
  - Global effect: demographics could subtract 0.1 of a percentage point from annual global growth over the next three decades (or 0.2 of a percentage point if early-dividend countries are unable to reap the demographic dividend).
- Migration role: In Australia, Hong Kong SAR, New Zealand, and Singapore, immigration—if past trends continue—could soften the impact of aging or prolong the demographic dividend.
- Methodology and baseline assumptions for growth accounting:
  - 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.
  - Baseline compares UN medium-fertility scenario (which includes migration) to a hypothetical status quo with constant population size and age structure; UN zero-migration scenario is considered separately.
- Baseline growth-impact examples (average, 2020–50 relative to status quo; Figure 2.5):
  - Japan: impact could reduce the average annual growth rate by almost 1 percentage point.
  - China: substantial negative impact (figure shows decline; chapter highlights China as largest absolute decline in working-age population: decline of 170 million over next 35 years).
  - Global impact shown as a purchasing-power-parity-weighted average as a percent of global GDP.

### Inflation and Macroeconomic Risks
- Structural excess savings and low investment due to demographics could lower the real neutral interest rate.
- If the real neutral rate falls so low that monetary policy can no longer stimulate the economy, the economy may operate below potential, keeping inflation under the central bank’s target.
- This raises the risk of Asia falling into a period of “secular stagnation” at a lower income level compared to advanced economies and with smaller policy buffers.
- Box 2.1 (Japan) is cited as an example of adverse demographic effects on monetary policy and inflation dynamics.

### External Flow Balance
- Diversity of demographic trends creates opportunities for capital flows and cross-border risk sharing: savings from surplus countries can finance capital needs in younger economies.
- IMF External Balance Approach (EBA) model projections:
  - Over the next decade, surpluses of some Asian economies are projected to increase due to demographics.
  - The impact is material only for a small set of countries.
  - The overall effect on global imbalances is likely to be limited: about 0.1 of a percentage point of global GDP over the next decade.

### Financial Markets
- Demographic trends are likely to put downward pressure on real interest rates and asset returns for most major countries in Asia.
- For financially open countries, domestic demographic effects are likely to be less important; changes in the world interest rate—possibly driven by global aging—will likely matter more.

### Policy Implications and Recommendations
- Adapting to aging is particularly challenging in Asia as many populations are becoming old at relatively low per capita income levels.
- Urgent priorities:
  - Protect vulnerable elderly populations.
  - Prolong strong growth through early adaptation of macroeconomic policies before aging sets in.
- Macroeconomic policy actions:
  - Secure debt sustainability.
  - Monitor potential changes in monetary transmission owing to aging.
- Structural and fiscal policy options (not exhaustive):
  - Labor market reforms: promote 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: develop new financial products to reduce precautionary savings and increase availability of “safe assets.”
  - Productivity-enhancing reforms: research and development and education (as discussed further in Chapter 3).
- Fiscal space can support these structural reforms.

### Additional Regional and Historical Context
- Between 1970 and 2010, Asia contributed more to the growth of the global working-age population than the rest of the world combined; this pattern is reversing as East Asian working-age populations decline.
- Absolute projected declines in working-age population (examples):
  - China: decline of 170 million in the working-age population over the next 35 years.
  - Substantial declines also projected for Japan, Korea, and Thailand.
- Contrast with other regions: April 2015 REO Sub-Saharan Africa projected that Africa will account for most of the growth in the global working-age population in coming decades.

*Prepared by Serkan Arslanalp and Jaewoo Lee (lead authors), Minsuk Kim, Umang Rawat, Jacqueline Pia Rothfels, Jochen Markus Schmittmann, and Qianqian Zhang.*

### 1. Impact on Real GDP Growth2. Impact on Real GDP Per Capita Growth

### 1. Impact on Real GDP Growth / 2. Impact on Real GDP Per Capita Growth

### Baseline growth impacts of demographic trends
- Post-dividend countries: demographic trends could reduce growth by ½ to 1 percentage point per year in absolute and per capita terms over the next three decades.
- Example country-level impacts (average, 2020–50): the drag for Japan is near 1.0 percentage point in each decade; for China the drag rises over time from 0.4 in the first decade to about 1.1 percentage points in the last decade.
- Sensitivity to fertility assumptions: compared to the UN’s medium-fertility scenario, the average annual growth rate is about 0.2 percentage point higher in the UN’s high-fertility scenario and about 0.2 percentage point lower in the low-fertility scenario.
- Migration effects on workforce size: the long-term UN assumptions on net migration rates for selected countries range from 2.5 percent in New Zealand to 6 percent in Australia.
- Illustration of required immigration to maintain dependency ratios by 2030: Australia would need immigration equal to approximately 23 percent of the actual workforce; Singapore would need approximately 51 percent.

### Per capita perspective
- Country ordering changes slightly on a per capita basis relative to aggregate growth impacts.
- The demographic drag is smaller for Japan on a per capita basis, but larger for Hong Kong SAR and Singapore because the positive impact of immigration is partially eliminated in the per capita perspective.

### Aging and Total Factor Productivity (TFP)
- Workforce aging measure: share of workers 55–65 years old in total workforce projected to increase substantially by 2050 in most Asian countries, with largest increases in China, Malaysia, and Vietnam (Figure 2.6).
- Evidence on productivity and aging:
  - Several studies 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).
  - Acemoglu and Restrepo (2017) find no robust negative impact of aging on productivity.
- Estimated effect of workforce aging on productivity for a sample of Asian and European countries: an increase in the share of older workers is associated with a significant reduction in labor productivity growth.
- Decomposition: 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 (see Annex 2.1).
- Estimated impact on GDP growth (average, 2020–50): 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).

### Sectoral and occupational differences
- Productivity-age profile varies by occupation (Veen 2008): productivity of workers in physically demanding professions tends to decline with age, while productivity may increase with age in professions such as lawyers, managers, and doctors.
- Low per capita income countries (e.g., Thailand, Vietnam) tend to have larger shares of workforce in occupations where productivity tends to decline with age, underscoring need for structural transformation.

### Labor Force Participation Rate (LFPR) scenarios
- Historical LFPR changes (1990–2015): overall LFPRs have remained remarkably stable, but with notable shifts across age-gender subgroups.
  - 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, notably Australia, New Zealand, and Singapore.
- Japan: LFPR increased close to 6 percentage points since 1990—the largest increase in the region.
- Scenario: if other Asian economies achieved a gradual increase in LFPR for all age and gender groups by 6 percentage points (based on Japan’s 1990–2015 experience), the impact on annual GDP growth is 0.2 to 0.3 of a percentage point.
- Larger LFPR changes: 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 (literature citations cited).

### Aging and investment (capital-to-effective-labor ratio)
- Baseline assumption: constant capital-to-effective-labor ratio.
- Empirical findings: workforce aging is associated with higher capital per worker (accounting for TFP), but the economic effect is small; no statistically significant relationship found between old-age dependency ratio and capital per worker.
- Conclusion: constant capital-to-labor-ratio assumption is a reasonable approximation for thinking about the next three decades.

### Welfare implication of sustained lower growth
- A sustained 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)
- EBA model captures demographic impact using population growth, old-age dependency ratio, and aging speed (expected change in old-age dependency in 20 years).
- Expected directional effects (Table 2.3):
  - Population growth: savings ↓, investment ↑, current account ↓.
  - Old-age dependency: savings ↓, investment ↓, current account ambiguous.
  - Aging speed: savings ↑, investment ↓, current account ↑.
- Empirical support: EBA model results support negative effect of population growth on current account and positive effect of aging speed on current account.
- By 2020–30 projections:
  - 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, Vietnam) will have very high speeds of aging until 2030; Australia and New Zealand will have lower speeds than the world average.
- Projected impact on current account norms (change from 2020 to 2030): demographics likely to exert upward pressure on current account balances in surplus countries (Japan, Korea, Thailand) given rising aging speeds; downward pressure among some deficit countries (notably New Zealand) given falling aging speed.
- Overall: demographics are projected to materially increase current account norms only for a select few countries in Asia; total impact on global imbalances is limited.

### Capital flow and multilateral implications
- Over 2020–30, changes in current account norms due to demographic trends are likely to be positively correlated with current account balances in 2015: countries with 2015 surpluses expected to remain capital exporters; those with deficits expected to remain capital importers.
- Caveat: estimates are partial-equilibrium and hold other macro variables fixed; broader interactions (e.g., with fiscal balance, productivity, output gap) could change magnitudes.

### Financial market implications
- Panel regression results on domestic interest rates, equity returns, and real estate prices indicate:
  - 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 impact of demographic factors on domestic real interest rates diminishes for countries that are financially more open.

*Source: areo0517c2 - 1. Impact on Real GDP Growth2. Impact on Real GDP Per Capita Growth (PDF chapter/section).*

### 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 drivers
- Long-term bond yields have declined significantly in Europe and the United States; Asia (particularly Australia and Korea) has seen a similar decline.
- 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.
- Evidence cited: estimated natural rates have declined dramatically in Europe, the United Kingdom, and the United States since the global financial crisis; in Asia, natural rates have fallen in advanced economies (Australia, Japan, and Korea) while remaining 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.

### Demographics and channels to interest rates
- Demographics can impact savings and interest rates primarily through:
  - Youth dependency
    - Mechanism: As youth dependency rises, the transition working-age cohort saves less, the 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
    - Mechanism: As old-age dependency rises, savings fall; as labor force shrinks, capital-to-labor rises and investment falls; theoretical impact on interest rates is ambiguous.
    - Old-age dependency is expected to rise relatively quickly in Hong Kong SAR, Korea, and Singapore.
  - Aging speed
    - Mechanism: Higher aging speed implies a higher probability of survival which, if not matched by later retirement, likely raises life-cycle savings and 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).

### Empirical findings on demographics and interest rates
- Empirical estimates support priors: youth dependency and aging speed affect interest rates; higher old-age dependency is found to reduce interest rates in the sample.
- Openness matters:
  - As economies become more open, the impact of domestic demographic factors on interest rates diminishes.
  - In the extreme case of perfect capital mobility, demographic factors have no direct impact on domestic interest rates.
  - In the analysis, the impact of youth dependency, old-age dependency, and aging speed becomes zero as an economy becomes perfectly open (based on the Chinn-Ito index).
- Magnitudes (expressed as ratios; effects for a fully closed economy):
  - A 1 percentage point increase in youth dependency increases the interest rate by 8.26 basis points when the economy is fully closed, while there is no impact in the case of a fully open economy.
  - Table of estimated coefficients (IMF staff calculations; 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

### Projected demographic impacts on real interest rates (2020–2030)
- Overall, demographic trends could put downward pressure on interest rates by about 1 to 2 percentage points in the next decade, all else being equal.
- The impact depends on:
  - Degree of openness
  - State of aging (early-dividend, late-dividend, post-dividend)
  - Speed of aging
- Country-specific patterns:
  - For fully open countries, demographic factors do not have a direct effect on domestic long-term interest rates.
  - Post-dividend countries (Korea and Thailand): rising old-age dependency is expected to depress interest rates.
  - Early-dividend countries (India and the Philippines): falling youth dependency is projected to reduce interest rates.
  - Aging speed slows in some cases (e.g., China and Australia), which can attenuate falls in interest rates by reducing savings and raising interest rates; aging speed increases in some young countries (e.g., India and Malaysia), driving down their interest rates.

### Other asset valuations: stocks and real estate
- The “asset market meltdown” hypothesis (baby boomer retirements causing sell-off pressure and sharp valuation declines) has mixed empirical support; historical U.S. and Japan experience is illustrative but evidence is not definitive.
- Conceptual channels:
  - Declines in youth dependency or rises in old-age dependency tend to lower interest rates, which would raise house prices; but they also reduce household formation and demand for housing.
  - Demographic changes can affect expected stock returns through risk-free rates and equity risk premiums; the net effect is conceptually 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.
  - Impact of domestic demographic factors on stock returns is partially offset by greater financial openness.
  - Links between demographic variables and real estate prices are weak empirically.
  - Openness plays an insignificant role for real estate, reflecting the local nature of housing markets.

### Policy implications and recommendations
- Broad priorities:
  - Early adaptation of macroeconomic policies before aging sets in.
  - Structural reforms in labor markets, pension systems, and retirement systems.
  - Productivity-enhancing reforms (for example, research and development and education).
- For early-dividend countries (India, Indonesia, and the Philippines):
  - Harness the demographic dividend and mitigate adverse spillovers from aging in the rest of Asia.
- For late- or post-dividend Asian countries:
  - Adapting to rapid aging at relatively low per capita income levels is urgent.
  - Policies should protect vulnerable elderly and seek to prolong strong growth.
- Macroeconomic policy recommendations:
  - Fiscal policy:
    - Introduce a credible medium-term fiscal framework to secure debt sustainability.
    - Shift the tax burden from labor to consumption.
    - Revamp the social safety net.
    - With a credible medium-term fiscal framework, fiscal policy can be used more actively in the short run given its higher potency in a low-interest-rate environment, including to support aging-related structural reforms.
  - Monetary policy:
    - Study how monetary transmission may change with aging (e.g., greater transmission through asset prices and household wealth rather than corporate borrowing costs).
    - Regular assessment of the neutral monetary stance is needed to avoid a potential tightening bias as the natural interest rate declines.
    - Prolonged low interest rates call for a strong macro-prudential framework to mitigate financial stability risks.
- Structural labor market reforms:
  - Raise labor force participation, especially for women and the elderly:
    - Expand child-care facilities, remove fiscal disincentives to dependents’ labor participation, 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.
    - Japan’s experience is highlighted as instructive.
  - Encourage foreign workers via targeted guest worker programs to address labor shortages and prolong demographic dividend benefits (examples: Australia, Hong Kong SAR, New Zealand, Singapore).
  - Promote active labor market policies:
    - Improve affordable health care for mature workers.
    - Facilitate human capital upgrading and retraining.
- Structural pension reforms:
  - Strengthen pension systems given rapid aging, fiscal costs, and relatively low pension coverage.
  - Entitlement reform through automatic adjustment mechanisms that link changes in retirement age (or benefits) to life expectancy to de-politicize pension reform and contain pension costs.
  - Note: Such rules have been introduced in many European countries; in Asia their use has been limited to date, except for Japan.

*Source: International Monetary Fund | April 2017.*

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

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

### Retirement systems and financial sector responses
- 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 is home to some of the largest public pension funds in the world (OECD 2016).
  - Reducing home bias—along the lines of recent Government Pension Investment Fund reforms in Japan—could help raise investment returns and secure more sustainable resources.
- New financial products could lower precautionary savings:
  - Reverse mortgages to help the elderly dissave post-retirement savings.
  - Annuities to insure against longevity risks.
- Cross-border risk sharing and financial integration opportunities:
  - Savings in late- or post-dividend countries seeking higher returns could finance large infrastructure gaps in early-dividend Asian countries (Ding, Lam, and Peiris 2014).
  - Increasing 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: 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 (April 2015 Regional Economic Outlook: Asia and Pacific).

### Japan: demographic headwinds — growth, inflation, and monetary policy
- Demographic facts and impacts:
  - Japan’s working-age population has been declining since 1997; overall population started to shrink only after 2010.
  - The falling working-age population together with change in overall labor force participation 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 (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 rate developments:
  - Female labor force participation rate 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.
  - These changes compare favorably to other G7 countries, including the United States (Figure 2.1.1).
- Demographics and inflation:
  - Shirakawa (2012): lower expected permanent income from demographic headwinds can trigger deflationary pressures as consumption and investment are cut.
  - Juselius and Takáts (2015): aging may increase inflation by constraining labor supply while dissaving by retirees keeps demand relatively stable.
  - A 1 percentage point increase in the old-age dependency ratio reduces the inflation rate by about 0.1 of a percentage point (Liu and Westelius 2016).
- Monetary policy effectiveness and secular stagnation:
  - Structural excess savings and a low neutral rate of interest may render monetary policy unable to stimulate the economy, keeping inflation below target.
- Policy implications for Japan:
  - Enhance labor supply by boosting female and older worker labor force participation and allowing for more foreign labor.
  - Reduce labor market duality.
  - Increase private investment to boost growth prospects, increase monetary policy effectiveness, and support fiscal sustainability.

### Fiscal implications of demographic trends in Asia
- Projected fiscal pressures:
  - 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, the increases would be driven by pensions.
- Public pensions projections:
  - Projected increases depend on each country’s position in the demographic transition and pension system characteristics.
  - Late- or post-dividend countries with defined benefit systems are likely to see larger increases.
  - For several late- or post-dividend countries (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 percent of GDP) are expected to remain broadly unchanged.
- Health care projections:
  - Increases depend on rise in old-age dependency ratios and 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.
  - Nozaki, Kashiwase, and Saito (2014) show that health care reforms in Japan 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.
  - Health care: options classified into three categories (Clements, Coady, and Gupta 2012):
    - Macro-level controls to cap spending (regulating price and quantity of health services).
    - Micro-level reforms to improve spending efficiency (promoting generic drugs and preventative care).
    - Demand-side reforms to curb demand (higher patient copayments and premium contributions).

### Annex 2.1 — Data and methodology: demographics, growth, and financial markets
- Demographics and labor supply:
  - Aggregate labor force projection based on United Nations World Population Prospects (the 2015 Revision, median-variant scenario):
    - Lt = Σj=1..J N_t^j LFP_t^j E_t^j w_t^j  (where symbols denote cohort counts, participation, employment, and weight factor).
- Demographics and labor productivity:
  - Methodology follows Aiyar, Ebeke, and Shao (2017) and Feyrer (2007).
  - Baseline model: Δ log YW_it = α1 w55_it + α2 DR_it + u_i + η_t + ε_it
    - YW = real output per worker; w55 = share of workforce aged 55–64; DR = dependency ratio; u_i = country fixed effect; η_t = decade fixed effect.
  - Endogeneity addressed by instrumenting workforce share and dependency ratio with lagged birth rates 10, 20, 30, and 40 years ago.
  - Data span 1950–2014; sample includes 12 Asian economies and more than 20 EU economies. Workforce and population from UN and OECD; output per worker from Penn World Table 9.0.
  - Result: 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 CA = CA(X_S, X_I, X_CA, X_CF, Z, ∆R).
  - Regression decomposition: CA = a + X' b + P' γ, with policy gap contributions measured as (P – P*)' γ.
  - Demographic variables included: population growth, old-age dependency ratio, interaction terms between old-age dependency and aging speed; old-age dependency ratio defined as population aged over 64 divided by population between 30 and 64.
  - Projections use UN World Population Prospects (2015 Revision, medium-variant scenario).
- Demographics and financial markets methodology:
  - Baseline panel regression for dependent variables r (10-year real interest rates), sr (year-over-year percent change in real stock returns), and pp (year-over-year percent change in real property prices):
    - 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
    - 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 for 10-year real interest rates model: GDP per capita relative to United States, growth in labor productivity, cyclically adjusted primary balance.
  - Controls for stock returns and property prices: growth in labor productivity.
  - Data sample spans 1985–2013. Interest rates model captures 42 economies globally (list in source).
- Annex Table 2.1.1 (Panel Regression: Demographics and Labor Productivity) — selected reported coefficients and statistics as presented:
  - Dependent Variables: Change in Real Output per worker; Change in Real Capital stock per worker; Change in human Capital per worker; Change in TfP (model based) per worker; Change in TfP (from PwT 9.0) per worker.
  - workforce share Aged 55–64:
    - 20.612*** (25.309)
    - 0.187*** 24.144
    - 20.0589*** (22.896)
    - 20.740*** (24.714)
    - 20.502*** (25.643)
  - dependency Ratio:
    - 20.122 (20.695)
    - 20.105 (21.532)
    - 0.0382 21.232
    - 20.0549 (20.229)
    - 0.279** 22.057
  - Observations: 571 for each specification.
  - Number of Countries: 33.
  - Note: t-statistics in parentheses. TfP = total factor productivity. ***p < 0.01; **p < 0.05; *p < 0.1.
  - Footnotes: Results are qualitatively similar with country and year fixed effects panel regressions. Model specification follows a Cobb-Douglas form for decomposition.

*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.
- The 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 econometric findings (summary of Annex Tables)
- Annex Table 2.1.2 (coefficients for 1986–2015):
  - Population Growth #: 20.565 20.659*
  - Old-Age dependency Ratio #: 20.057 20.091*
  - Rel. Old-Age dependency Ratio 3 Aging speed #: 0.130*** 0.103***
  - Rel. Aging speed 3 Old-Age dependency Ratio #: 0.088** 0.106**
- Annex Table 2.1.3 (Panel Regression: Demographics and Long-Term Interest Rates, Stock Returns, and Property Prices) — selected coefficients and significance (standard errors in parentheses):
  - Dependent: 10-Year Real Interest Rate
    - Youth dependency Ratio: 9.41*** (2.46)
    - Youth dependency Ratio 3 Capital Openness: 27.96*** (1.96)
    - Old-age dependency Ratio: 218.3*** (6.28)
    - Old-age dependency Ratio 3 Capital Openness: 17.04*** (5.77)
    - Aging speed: 229.7*** (11.06)
    - Aging speed 3 Capital Openness: 25.89** (10.09)
    - world Interest Rate: 0.65*** (0.16)
    - Growth in Labor Productivity: 0.07 (0.06)
    - Constant: 2.660*** (0.214)
    - Observations: 740; Number of Groups: 42
  - Dependent: Percent Growth in stock Return
    - Youth dependency Ratio: 67.28*** (23.66)
    - Youth dependency Ratio 3 Capital Openness: 231.01** (14.22)
    - Old-age dependency Ratio: 232.69 (82.26)
    - Old-age dependency Ratio 3 Capital Openness: 138.26* (75.02)
    - Aging speed: 315.31* (163.18)
    - Aging speed 3 Capital Openness: 2317.04** (142.92)
    - world Interest Rate: 21.18 (2.17)
    - Growth in Labor Productivity: 4.75*** (0.98)
    - Constant: 10.15*** (0.967)
    - Observations: 406; Number of Groups: 45
  - Dependent: Percent Growth in Real Property Price
    - Youth dependency Ratio: 211.32*** (3.96)
    - Youth dependency Ratio 3 Capital Openness: 0.67 (4.00)
    - Old-age dependency Ratio: 253.18* (31.77)
    - Old-age dependency Ratio 3 Capital Openness: 25.37 (26.99)
    - Aging speed: 2100.95*** (34.05)
    - Aging speed 3 Capital Openness: 60.79* (31.86)
    - world Interest Rate: 1.48*** (0.53)
    - Growth in Labor Productivity: 0.30 (0.20)
    - Constant: 1.759*** (0.405)
    - Observations: 716; Number of Groups: 56
  - Note: ***p < 0.01, **p < 0.05, *p < 0.1.

- Annex Table 2.1.5 (Panel Regression: Demographics and Long-Term Interest Rates — alternative specification where effects vanish with perfect openness):
  - Youth dependency Ratio 3 (1 2 Capital Openness): 8.26*** (1.95)
  - Old-Age dependency Ratio 3 (1 2 Capital Openness): 216.16*** (5.51)
  - Aging speed 3 Capital Openness: 229.26*** (9.87)
  - world Interest Rate: 0.84*** (0.11)
  - Ratio of GdP per Capita to that of the Us: 2.43* (1.39)
  - Growth in Labor Productivity: 0.07 (0.06)
  - Constant: 20.63 (1.57)
  - Observations: 740; Number of Groups: 42

### Interpretation of interaction with capital openness
- Results indicate that on long-term interest rates and stock returns, the impacts of domestic demographic factors tend to diminish as the country becomes more open.
- On property prices, the effect of capital openness is small and insignificant, reflecting the local nature of the market.
- Combining results shows that the impacts of all youth and old-age dependency ratios and aging speed become almost zero as an economy becomes perfectly open (Annex Table 2.1.5).

### Robustness and time-series properties
- Because demographic variables evolve slowly, tests for unit roots were conducted (Annex Table 2.1.6).
  - Residuals from baseline regressions reject the null hypothesis of a unit root (Fisher and Im, Pesaran and Shin tests), implying no evidence of spurious regression for the baseline residuals.
  - Individual variables:
    - Real Interest Rate: I(0) under both Constant and Trend specifications.
    - Youth Dependency: I(0) under Constant; Trend inconclusive.
    - Old Dependency: I(1) for Constant and Trend.
    - Aging Speed: I(1) for Constant and Trend.
    - World Interest Rate: I(1) for Constant and Trend.
    - Residuals: I(0).
  - Figures in parentheses in Annex Table 2.1.6 are p-values for the test under the null hypothesis of nonstationarity. One lagged difference included.

### Long-horizon evidence
- Annex Table 2.1.7 (Annual Model, 3-Year Averages, 5-Year Averages) — coefficients broadly consistent with baseline:
  - Youth dependency Ratio: 9.41*** (Annual), 9.68*** (3-Year), 9.33** (5-Year)
  - Youth dependency Ratio 3 Capital Openness: 27.96***, 28.14***, 27.20**
  - Old-Age dependency Ratio: 218.30***, 221.10**, 217.00
  - Old-Age dependency Ratio 3 Capital Openness: 17.04***, 19.21**, 18.53*
  - Aging speed: 229.69***, 225.56, 235.48*
  - Aging speed 3 Capital Openness: 25.89**, 20.69, 28.46*
  - world Interest Rate: 0.65***, 0.61**, 0.46
  - Observations: 740 (Annual), 271 (3-Year), 166 (5-Year); Number of Groups: 42

### Natural interest rate methodology and results (related context)
- Natural rate estimated using a time varying parameter VAR (TVP-VAR) on real GDP growth, inflation, and a measure of real interest rate; 5-year forecast of observed real rate used as measure of the natural rate.
- Data span: 1970:Q1 – 2016:Q4 (varies by country).
- 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.

*Source: IMF staff estimates, Regional Economic Outlook: Asia and Pacific, April 2017 (Annex Figures and Tables).*

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_Source: https://www.imf.org/-/media/files/publications/reo/apd/2017/areo0517c2.pdf_