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The Average Propensity to Consume Out of Full Wealth: Testing a New Measure. Full Wealth: The Right Measure of Wealth for Consumption. Lifecycle/PIH theory since Modigliani says consumption should depend on all current and future resources (including financial and human wealth.)
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The Average Propensity to Consume Out of Full Wealth: Testing a New Measure
Full Wealth: The Right Measure of Wealth for Consumption • Lifecycle/PIH theory since Modigliani says consumption should depend on all current and future resources (including financial and human wealth.) • Essentially a stock value of permanent income from today forward • I call this PDV of all resources: “Modigliani full wealth” = M
Unprecedented Ability to Measure Full WealthHealth and Retirement Study • Expected present value of resources: M = Net Worth + Human Wealth • Net Worth = 10 categories of assets less 3 categories of debt • Human Wealth= Earnings+Pensions+Social Security+Other Transfers (deterministic for older households)
Outline • Full wealth: How it’s different • by age profile, variance, and distribution • The APC out of full wealth: C/M (Comparing C/M to C/NetWorth and C/Income) • What to expect from C/M theoretically • More tightly distributed • More consistent over time • Relatively invariant to circumstances and shocks • Empirical Results
Age Profile of Wealth Full Wealth is Not Just Scaled-Up Net Worth Full Wealth Net worth
Full Wealth Has Less Variance… Coefficients of Variation
…and is more equally distributed Lorenz Curves Full Wealth Net worth
The Average Propensity to Consume Out of Full Wealth Neoclassical model: • C proportional to M • Very limited sources of variation in C/M across households • C/M changes only slowly over time (from mortality, changes in returns expectations, or changes in preferences) • C/M does not change with income shocks if consumption responds quickly
Which Implies… C/M relative to C/NetWorth or C/Income Should Have: • Lower variance • Higher covariance over time • Lower correlation with “circumstances” such as: • Having a pension or the generosity of pension and social security benefits (income replacement rate in retirement) • Earnings profile over lifetime • Having children • Income Shocks Also ∆(C/M) Should Have: • Lower correlation with income shocks (also proxied by employment and health shocks)
And the data says… Lower and more consistent variance Higher covariance over time
Circumstances • Traditional savings or consumption rates (C/I) have “noise” from circumstances, both cross-sectionally and longitudinally • Examples: • Households expecting generous DB pension income will save less than otherwise identical households with little or no DB pension • Households experiencing a temporary positive income shock will save more that period
How much of C/I is explained by circumstances? If C/M is a cleaner measure of true consumption rates… Then a low covariance between C/I and C/M means a lot of noise in C/I from circumstances Cov = 0.31
Cross-Section or Level of C/M:Less Correlated with Many Circumstances • Circumstance: Generosity of retirement benefits (DB pension and Social Security) • Measure: RetRatio: Ratio of PV(Pension+Social Security) to Average Earnings Over Ages 45-55 • Outcome: C/M is less correlated
…Cont Income Profile • Circumstance: Income Profile • Measure: Average slope of household earnings during 30s, 40s, 50s & early 60s • Outcome: C/M uncorrelated; C/NW & C/I have some significant correlation
…ContHaving Children • Circumstance: Children • Measure: Dummy variable for having any children • Outcome: C/M less correlated for 2001; both uncorrelated in 2003
…ContIncome Shocks • Circumstance: Past Income Shock • Measure: Change in Earnings over previous years • Outcome: C/M less correlated than C/I; results mixed comparing C/M with C/NW
Time-Series: Change in C/M • Previous tables showed relative invariance of the level of C/M to circumstances, including income shocks • The change in C/M should also be invariant to income shocks if C responds relatively quickly to new information.
Instrument that affects M ex-post: Show it does not affect C/M • Note: Not sure about this, still working on it. • I’ve thought about employment shock (unexpected retirement between 2001 & 2003 or unemployment in 2002) but survey timing of C and M makes this difficult • Rate of return shock problematic b/c can’t separate portfolio changes from returns – especially relevant in 2000-2003 when people probably changed their portfolio
Conclusion Full Wealth and the APC out of Full Wealth: • Empirically match expected distribution characteristics • The level of C/M has less correlation with circumstances than either C/NW or C/I • The change in C/M is relatively invariant to recent shocks when compared to C/NW or C/I