How Do Household Portfolio Shares Vary With Age? John Ameriks The Vanguard Group john_ameriks@vanguard.com Stephen P. Zeldes Benjamin Rosen Professor of Finance & Economics Graduate School of Business Columbia University stephen.zeldes@columbia.edu/ www.columbia.edu/~spz1 Presentation notes: October 2005 Fall 2005 Q-Group Seminar
Introduction and motivation • How households allocate their financial portfolios is an increasingly important issue to economists, policymakers, and investors • Shift from DB to DC in pensions • Increasing emphasis on accounts/asset ownership as a policy solution • Aging of the population
Our focus is on variation with age • How should portfolio allocations change with age? • How do portfolio allocations change with age? • We examine both questions, but focus on the second
Outline • Economic theory, professional prescriptions, and previous evidence • Modeling and identification • Data • Results • Conclusions
Economic Theory: Benchmark Model • Mossin, Samuelson, Merton c. 1968 • Assumptions • No labor income or non-tradable assets • Stock returns i.i.d. • CRRA utility, time invariant, time separable • No transactions costs or other market frictions • Benchmark Result: Fraction of wealth optimally held in stock is constant, and thus independent of both age and wealth
Economic Theory: Extensions • Human capital • Key issue is correlation of labor income with stock market • Non-i.i.d. asset returns (mean reversion, other patterns) • Other utility functions (changing risk aversion, non- separability, others) • Transactions costs (Learning, monitoring, information, taxes, fees) • See Jagannathan and Kocherlakota (1996), Gollier (2004)
Professional Advice: The longer the investment horizon, the greater the equity share should be • Typical rule of thumb: Stocks/financial assets = 100 – age Share of assets in stocks vs age 100 80 percent in stocks 60 40 20 0 0 20 40 60 80 100 age
“Life-cycle” / “target date” mutual funds • Automatic reduction in equity share (½ - 3 percentage points per year) • Growing in popularity • Currently ~ $45-50 billion in target date funds • Examples include: • Vanguard “Target Retirement” funds • Fidelity “Freedom Funds” (2010, 2020, 2030) • Barclays Global Investors (“LifePath Funds”) • T. Rowe Price Funds • TIAA-CREF Funds
Findings of Previous Studies • Agnew, Balduzzi, and Sunden (AER, 2003) “ Age has a negative effect on the share held in equities: each extra year translates into a lower allocation to stocks by 93 basis points. This is remarkably close to the practitioners’ rule of thumb of decreasing one’s equity exposure by 1 percent for each additional year of age.”
Modeling and identification • Solution to optimal portfolio choice problem will be of the form ω it = f (a it , b i , t, W it , Z it ) where: ω it = share of financial wealth in equities a it = age of person i at time t b i = birth year of person i t = calendar time W it = financial wealth of person i at time t Z it = other state variables and person-specific characteristics
Age, time, and cohort effects • Well known identification problem • Arises in many literatures, particularly labor
Age, time, and cohort effects • Age effects : the change in ω it caused by a change in a it • How much does the optimal equity share change as a result of an individual being one year older? • Time effects : the change in ω it caused by a change in t • How much does the optimal equity share at time t differ from that at time t-1? • Technology changes, changing cost structures, shifting expectations, or other time-specific developments • Cohort effects : change in ω it caused by a change in b i • How much does the optimal equity share of someone born in 1970 differ from that of someone born in 1969 (regardless of time or age)? • Could be that those with differing experiences behave differently, (e.g. some have memories of depression or 1970’s)
Age, time, and cohort effects (cont.) Problem: a it ≡ t - b i , so impossible to separately identify these without further assumptions. • Figs 1 – 3 show that different stories can be consistent with the same data
Figure 1 Hypothetical Portfolio Share Data 0.64 0.63 Fraction of assets in equity 0.62 0.61 0.60 0.59 39 40 41 42 43 44 45 46 47 48 49 50 51 Age
Figure 1 Hypothetical Portfolio Share Data flat Cross section view: 0.64 Time no age no cohort 0.63 effect, effect, effect Fraction of assets in equity Cross section 0.62 view (Time t + 2) Cross section 0.61 view (Time t + 1) Cross section 0.60 view (Time t ) 0.59 39 40 41 42 43 44 45 46 47 48 49 50 51 Age
Figure 1 Hypothetical Portfolio Share Data Cohort view: rising 0.64 cohort age no time 0.63 effect, effect, effect. Fraction of assets in equity 0.62 0.61 0.60 Cohort Cohort Cohort view view view 0.59 39 40 41 42 43 44 45 46 47 48 49 50 51 Age Note that this explanation requires 2 effects, previous only 1
Figure 2 Hypothetical Portfolio Share Data Cross section view: declining Cohort view: flat 0.63 cohort no age no time 0.62 effect, effect, effect 0.61 or Fraction of assets in equity Cohort 0.60 view time age no cohort effect, effect effect. , 0.59 Cohort 0.58 view 0.57 Cohort Cross section view 0.56 view (Time t + 2) Cross section view 0.55 (Time t + 1) 0.54 Cross section view (Time t ) 0.53 54 55 56 57 58 59 60 61 62 Age
Data: Surveys of Consumer Finances • 1962 (SFCC), 1983, 1989, 1992, 1995, 1998 • Excellent balance sheet data on representative sample • Includes data on • demographic characteristics • wealth inside and outside of pensions • Summary statistics (Table 1) • Average portfolio shares (Table 2)
Data: TIAA-CREF • Large sample (~16,000) of TIAA-CREF participants • Up to 13 years (52 quarters) of administrative data on • Contributions, accumulated balances, transfers • Smaller sample (~2000 individuals) with one- time survey of demographics and assets outside of TIAA-CREF, linked to 10 years of quarterly administrative data.
Data: TIAA-CREF • Advantages • Actual account balances and transaction activity (from TIAA- CREF), not based on survey responses • Track same people over time • Data on both “stock” of accumulated assets and “flow” of new contributions • Disadvantages • Not representative of US population • Limited info on demographics / assets outside of TIAA-CREF • Individuals rather than households • Institutional rules and changes may affect behavior (e.g. transfer restrictions)
NEW Data: Vanguard IRA Holders • Data on population of Vanguard clients with assets in tax-deferred individual accounts, excluding employer plans, as of 12/31/2004. • Limit to those with at least $5,000 in one fund account at end 2004. • Tax-deferred balances only • ~ 2 million records at end 2004 • Historical balance data back to 1998, reconstructed from transactional records • VERY PRELIMINARY
Results • First, we document three important features of household portfolio behavior
Non-stockownership • About half of U.S. households do not own stock (Table 6), but • The fraction of households owning stock has risen substantially Percentage of US households owning stock 1962 1989 1992 1995 1998 2001 ~23.9% 33.3% 37.6% 41.3% 49.4% 52.2% • ~70% of non-stockowners own little financial wealth, but the rest do have financial wealth (Table 7) • 20% of TIAA-CREF participants owned no stock in 1987 – by 1999, less than 15% own no stock
Heterogeneity in choices • TIAA-CREF Flows • Wide range of allocations is used • Clustering at specific points (0, 25, 50, 75, 100)
Infrequency of changes (Table 8) over 40 quarters • People who make asset reallocations also tend to make flow reallocations
Results on age patterns • Age patterns in level of equity share • assets (SCF, TIAA-CREF) • flows (TIAA-CREF) • For each, examine • Unconditional equity share • Probability of ownership • Equity share conditional on ownership
Figure 10 Equity Share in Assets TIAA-CREF Data 1987-1999
Figure 11 Fraction of Participants with Equity in Assets TIAA-CREF Data 1987-1999
Figure 12 Equity Share in Assets Among Equity Holders TIAA-CREF Data 1987-1999
Figure 13 Equity Share in Flows TIAA-CREF Data 1987-1999 Note large increases in equity share of young people in the 1990’s. Equity share in contribution flows of individuals aged 28-30 1990 1999 31% 73%
Unconditional Equity Shares in Assets Vanguard Retirement Account Holders, 1998-2004 • Higher equity shares vs. TC data • Influence of time effects/markets is again apparent • Largest changes appear to have occurred among the OLD • As of 2004, the older cohorts are holding MORE equity than in 1998.
Ownership of Equity in Assets Vanguard Retirement Account Holders, 1998-2004 • Ownership changes are still important • Not as dramatic as in earlier data • > 70% of those in their 70s still own some equity • Ownership actually rose in older cohorts
Recommend
More recommend
