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

Full Wealth is Not Just Scaled-Up Net Worth

Age Profile of Wealth

20

0,0

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40

0,0

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60

0,0

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80

0,0

00

10

0000

0

55 60 65 70 75Age of Household Head

Full Wealth Cash-on-Hand Net Worth

Full Wealth

Net worth

Full Wealth Has Less Variance…

Coefficients of Variation

CV Mean

Full Wealth 0.96 $825,000

Net Worth 1.67 $322,000

Income 1.21 $61,600

Consumption 0.77 $40,300

…and is more equally distributed0

.2.4

.6.8

1

0 .2 .4 .6 .8 1Cumulative population proportion

Lorenz Curve Full Wealth Lorenz Curve Net Worth

Full Wealth

Net worth

Lorenz Curves

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…

Std. Dev. Mean Median CV

C/M 2001 .058 .078 .060 0.74

C/M 2003 .062 .084 .067 0.74

C/NW 2001 3.26 1.05 .221 3.10

C/NW 2003 12.56 2.59 .256 4.85

C/I 2001 1.47 1.22 .828 1.20

C/I 2003

Lower and more consistent variance

Higher covariance over time

Covariance 2001&2003

C/M 0.70

C/NW 0.37

C/I

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

.02

.06

.1.1

4

C/M

.5 1 1.5 2 2.5C/Income

Income vs. Full WealthScatter Plot of Consumption Rates:

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

Bivariate OLS Coefficient & T-stat R2 Const

ln(C/M) 2001 on RetRatio .0032** (2.4) .004 -2.86

ln(C/NW) 2001 on RetRatio

.0159*** (6.0) .025 -1.58

ln(C/M) 2003 on RetRatio .0014 (0.9) .001 -2.79

ln(C/NW) 2003 on RetRatio

.0154*** (5.0) .025 -1.52

…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

Dependent Variable→ ln(C/M) ln(C/NW) ln(C/I)

Independent Variables↓

2001 Earning slope 30s -.067 (-1.3) -.267** (-2.2)

-.111* (-1.9)

Earning slope 40s .059 (1.3) .220** (2.4) -.001 (-0.1)

Earning slope 50s .060 (1.1) .049 (0.4) -.073 (-1.2)

Earning slope early 60s -.049 (-0.6) .029 (0.2) -.222** (-2.2)

Separate Regressions:

2003 Earning slope 30s -.074 (-1.4) -.050 (-0.5)

Earning slope 40s .037 (0.8) .238*** (2.8)

Earning slope 50s .019 (0.4) .187* (1.7)

Earning slope early 60s -.022 (-0.2) -.183 (-0.8)

…ContHaving Children

• Circumstance: Children• Measure: Dummy variable for having any children • Outcome: C/M less correlated for 2001; both

uncorrelated in 2003

OLS Coefficient T-stat R2 Const

ln(C/M) 2001 on Children -0.102* -1.73 .002 -2.73

ln(C/NW) 2001 on Children -0.302** -2.32 .005 -1.16

ln(C/M) 2003 on Children 0.064 0.94 .001 -2.83

ln(C/NW) 2003 on Children -0.109 -0.73 .001 -1.22

…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

Dependent Variable→ ln(C/M) ln(C/NW) ln(C/I)

Independent Variables↓

2001 Y Shock 2000-2001 .086** (2.0) .138* (1.6) -.141*** (-3.2)

Y Shock 1999-2000 -.034 (-0.7) -.086 (-0.8) -.168*** (-3.3)

Separate Regressions:

2003 Y Shock 2000-2001 .076 (1.3) -.069 (-0.6)

Y Shock 1999-2000 .014 (0.2) .088 (0.7)

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.

Change in C/M Less Correlated With Shocks

Dependent Variable→ ∆(C/M) ∆(C/NW) ∆(C/I)

Independent Variables↓

Y Shock 2000-2001 -.050 (-1.3) -.175** (-2.0)

Y Shock 1999-2000 .001 (0.0) .044 (0.4)

Separate Regressions:

Recent Past Negative Employment Shock

-.132 (-1.5) -.429** (-2.3)

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