The Impact of Global Aging on Saving, Investment, Asset Prices, and Returns for the Q Group The Institute for Quantitative Research in Finance Gary Burtless The Brookings Institution Washington, DC USA October 18, 2005 Carlsbad, California
Population ageing is occurring in nearly all countries In rich countries, aged population obtains much of its income & consumption from government budgets Populations in both rich and poor countries are growing older Falling mortality rates / Longer life expectancy Declining fertility Immigration is variable & uncertain
Impact of ageing on financial markets and the economy Relative declines in rates of saving and investment Will aged societies be net lenders or net borrowers (current account balance)? Implications for asset prices and returns Open-economy aspects Current account balance (national saving less domestic investment) Interaction with demographic change
Life-cycle consumption theory: Age profile of saving Annual earnings and consumption 25,000 Earnings 20,000 15,000 10,000 Consumption 5,000 0 20 30 40 50 60 70 80 Age The difference is annual saving or dissaving.
Life-cycle consumption theory: Wealth accumulation Wealth 200,000 150,000 100,000 50,000 0-50,000 20 30 40 50 60 70 80 Age
Do changes in the age structure have the impact on aggregate household saving implied by the life-cycle hypothesis? Microeconomic analysis Weak life-cycle influences Many people have no significant retirement saving Highly disparate patterns of wealth accumulation complicates aggregation Average dollar, not average person Wealthy savers have out-size effect on aggregate saving Importance of cohort effects
Life-cycle consumption theory: Cross-Section Data Factor income received by average 45-49 year-old = 100 120 100 88 94 100 103 94 Capital income Labor income 80 60 62 59 77 71 81 85 88 87 74 72 49 40 20 0 48 38 33 32 31 26 32 21 20 7 6 10 6 3 2 3 15-19 25-29 35-39 45-49 55-59 65-69 75-79 85-89 Age group: United States
Age pattern of U.S. saving rates: Consumption Survey Results Saving measured as after-tax income minus consumption expenditures (CEX) 18 Percent of after-tax income 16 14 12 10 8 6 4 2 9.6 8.6 10.6 15.8 11.5 10.8 0 25-34 35-44 45-54 55-64 65 and older Total sample Age group Source: Bosworth, Burtless & Sabelhaus (1991).
Age pattern of U.S. saving rates: Wealth Survey Results Saving measured as change in wealth minus estimated capital gains (SCF) 16 Percent of after-tax income 14 12 10 8 6 4 2 0 13.6 10.1 10.3 10.6 25-34 35-44 45-54 55-64 65 and older Total sample 2.5 9.5 Age group Source: Bosworth, Burtless & Sabelhaus (1991).
Macroeconomic analysis Shows stronger evidence of demographic effects on saving Most pronounced for Asia Results for industrial economies sensitive to countries and time period. But the aggregate trend in personal saving often contradicts theory s prediction: U.S. saving has declined since mid-1980s. Multi-country panel data sets Cross-national differences are correlated with other determinants. Within-country demographic changes are small compared to changes in saving
Do changes in the age structure have the impact on investment demand implied by the life-cycle hypothesis? Slower labor force growth should reduce growth of required capital stock. Limited research on link between labor force growth and technical change
There are only a few studies of impact of aging on investment demand. Higgins (1998) concludes that the decline in investment will exceed that of saving for highincome economies out to 2025. Bosworth and Keys (2004) also obtained strong demographic effects, but -- Decline in saving projected to exceed that of investment by 2050 High-income countries would have current account deficits.
Do changes in the age structure have a significant impact on asset prices? Asset prices assumed to vary in response to changes in the capital-output ratio. Price of capital assumed to depend on marginal product, or relative scarcity Age-related demand for assets Mankiw-Weil (1989) Housing Demographically determined asset prices
Problem with Mankiw-Weil prediction Annual rate of change in housing prices (5-year lagged moving average) Estimation period Demographic measure of "change in housing demand" Prediction 5.0% 4.0% 3.0% 2.0% 1.0% 0.0% -1.0% -2.0% -3.0% -4.0% -5.0% Change in price (left axis) Change in demand (right axis) 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2.6% 2.4% 2.2% 2.0% 1.8% 1.6% 1.4% 1.2% 1.0% 0.8% 0.6% 0.4% 0.2% 0.0% Source: Bosworth, Bryant & Burtless (2004). Year
Pension fund accumulation and decumulation Schieber-Shoven (1997) Age-related portfolio preferences Poterba (2001) and Davis and Li (2003) Proportion of portfolio devoted to risky assets rises up to age 60, but does not decline much thereafter Effects of demographic structure on returns varies across countries
Age pattern of household portfolios: Risky asset as % of net financial assets (U.S.A.) Common stocks as a percent of net financial assets 60 50 40 30 20 22 33 36 41 53 50 42 45 38 33 31 27 10 0 0 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75+ Age group Source: Poterba (2001).
Age pattern of household portfolios: Risky asset as % of household net worth (U.S.A.) Common stocks as a percent of net worth 20 18 16 14 12 10 8 6 4 2 0 18 17 16 16 16 15 15 12 9 10 6 0 3 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75+ Age group Source: Poterba (2001).
Age pattern of household net worth: Tabulations of U.S. Survey of Consumer Finances (1983-1995) Net worth (1995 dollars) 210,000 180,000 150,000 120,000 90,000 60,000 30,000 0 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75+ Age group Source: Poterba (2001).
Research Agenda Saving There is a large disconnect between the micro and macroeconomic research on saving Investment Panel data for large sample of countries in order to refine estimates of demographic effects Linkage between labor force growth and technological change Asset Prices Improve the microeconomic data to incorporate pension funds
Cross-Border Impacts of Aging
Enhanced Cross-Border Economic Integration 2 sets of underlying causes: Technological innovations and social/cultural changes reducing economic and psychic distances between nations Lowering of barriers at borders 2 secular trends in cross-border substitutabilities : Goods: household and firms more willing to substitute home and foreign goods in response to relative price changes Financial: savers and investors responding more strongly across borders or currencies to changes in relative expected returns
Implications for an Economy s Saving-Investment Balance Macroeconomic variables more closely linked across borders than before Macroeconomic adjustments channeled relatively more through external-sector transactions; cross-border and cross-currency adjustments more important relative to domestic adjustments Hence larger swings in current-account balances due to heightened goods and financial substitutabilities Larger imbalances occur, not only ex ante but also ex post, between national saving and domestic investment
Main conclusion to keep in mind As economies become more open, there may be a reduction in the correlation between domestic investment and national saving. Equivalently, there may be a tendency for current-account imbalances to become larger and more variable. Hence cross-border and cross-currency adjustments to policy and non-policy shocks rise in importance relative to purely domestic adjustments.
Demographic Shocks in Open Economies Different pace and intensity of demographic change in the world, among developed economies, and especially between industrial and developing countries External-sector transactions, exchange rates and variations in current account balance are important parts of macroeconomic adjustments to demographic shifts
Uneven pace of population ageing across countries Fast-ageing areas Europe Korea Japan Slow pace of ageing Indonesia Nigeria Philippines Intermediate pace USA / Canada Australia Latin America
Unequal change in old-age dependency Old-age dependency ratio (Ratio of people 65 years old and older to persons age 20-64) 80 70 60 50 40 30 Japan 78.2 Russia Thailand USA Japan 20 10 0 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 Year 38.2 Thailand Source: U.N. Population Projections (2004).
Demographic Shocks in Open Economies A nation s dependency ratios youth and elderly may be correlated with variations of its current account (S-I) balance International capital flows and externalsector goods transactions can cushion some of the impacts of demographic change on domestic macroeconomic variables.
Conclusions -- Micro & macro studies find age profile roughly corresponds to life-cycle prediction BUT micro studies show smaller effect of aging possibly because pension saving is missed in micro studies Recent saving trends in many industrialized countries don t fit the theory: Aggregate saving has dropped in spite of more middle-aged savers Slower growth in working-age population should depress investment demand Whether declining saving or shrinking investment demand will have bigger effect is open question
Conclusions -- Different age groups have different preferences for risky & non-risky assets In theory, this could mean that aging will influence demand for different asset classes and expected returns Micro & macro studies have found age effects on asset holdings and returns of different asset classes In micro studies, demand for risky assets among very aged implies little if any decline in overall demand for risky assets in foreseeable future Macro studies fail to uncover consistent pattern of change in asset demand with aging My guess: The predictable impact of age structure on asset demand is small relative to unpredictable sources of change