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The Average Propensity to Consume Out of Full Wealth: Testing a New Measure Laurie Pounder.

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Presentation on theme: "The Average Propensity to Consume Out of Full Wealth: Testing a New Measure Laurie Pounder."— Presentation transcript:

1 The Average Propensity to Consume Out of Full Wealth: Testing a New Measure Laurie Pounder

2 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

3 Unprecedented Ability to Measure Full Wealth Health 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)

4 Full Wealth is Not Just Scaled-Up Net Worth Age Profile of Wealth Full Wealth Net worth

5 Full Wealth Has Less Variance… Coefficients of Variation CVMean Full Wealth0.99$738,100 Net Worth1.68$324,300 Income1.24$62,100 Consumption0.76$40,300

6 …and is more equally distributed Full Wealth Net worth Lorenz Curves

7 The Average Propensity to Consume Out of Full Wealth Lifecycle model: Very limited source 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

8 Which Implies… Relative to C/Income or C/NetWorth, C/M Should Have: Lower variance Higher covariance over time Lower correlation with “circumstances” such as: –Income Profile Having a pension or the generosity of pension and social security benefits (income replacement rate in retirement) Earnings profile over lifetime –Past Income Shocks Also ∆(C/M) Should Have: Lower correlation with past shocks both to income and to full wealth

9 And the data says… Std. Dev.MeanMedianCV C/M 2001.058.078.0600.74 C/M 2003.062.084.0670.74 C/NW 20013.261.05.2213.10 C/NW 200312.562.59.2564.85 C/I 20011.471.22.8281.20 C/I 20031.371.24.8881.10 Lower and more consistent variance

10 Covariance 2001&2003 C/M0.70 C/NW0.37 C/I0.27 And higher covariance over time

11 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

12 Lifecycle Model Illustrations

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14 Comparison of Baseline to Household with Lower Retirement Income

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17 Income Shocks

18 Comparison of Baseline and Shocked Household

19 Testing 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

20 Retirement/Earnings Ratio Bivariate OLS Coefficient & T-stat R2 std(C/M) 2001 on RetRatio0.003 (1.2) 0.00 std(C/NW) 2001 on RetRatio0.013*** (6.0) 0.03 std(C/I) 2001 on RetRatio0.005** (2.1) 0.01 std(C/M) 2003 on RetRatio-0.001 (-0.4) 0.00 std(C/NW) 2003 on RetRatio0.016*** (4.8) 0.03 std(C/I) 2003 on RetRatio0.007** (2.3) 0.01 Coefficients represent fraction of standard deviation from mean so can be compared across dependent variables

21 Income Shocks  Circumstance: Past Income Shock  Measure: Change in Earnings over previous years  Outcome With Levels: results mixed: C/M less correlated than C/I in 2001; less correlated for large shocks in 2003

22 Income Shocks on Levels of Consumption Rates 2001 Dependent Variable → std(C/M)std(C/NW)std(C/I) Independent Variables↓ Y Shock 2000-20010.163** (2.0)0.124* (1.6)-0.263***(-3.2) Y Shock 1999-2000-0.064 (-0.7)-0.077 (-0.8)-0.314***(-3.3) 2003std(C/M)std(C/NW)std(C/I) Y Shock 2001-2003-0.003 (0.6)0.004 (0.4)-0.008 (-1.3) Y Shock 2000-20010.135 (1.4)-0.079 (-0.8)0.094 (1.0)

23 2003 with Large Shocks 2003std(C/M)std(C/NW)std(C/I) >25% Negative Y Shock 2001-2003 -0.103 (-0.9) -0.314*** (-2.7) 0.641*** (6.1) >25% Positive Y Shock 2001-2003 0.085 (0.9) 0.161* (1.7) -0.390*** (-4.4) >25% Negative Y Shock 2000-2001 0.028 (0.2) -0.310** (-2.3) 0.311** (2.5) >25% Positive Y Shock 2000-2001 0.126 (1.0) -0.073 (-0.6) -0.020 (-0.2)

24 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).400*** (6.2) Y Shock 1999-2000.001 (0.0).044 (0.4).168** (2.4)

25 Changes in M Since M is an expected value of current and future resources, any change in M must be unexpected, unlike a change in income If consumers adjust relatively quickly to changes in M, then C/M should be relatively invariant to such changes Instrument for change in M: Unexpected retirement

26 Change in C/M Less Affected by Unexpected Changes in M Dependent Variable→ ∆(C/M)∆(C/NW)∆(C/I) Independent Variable↓ Unexpected Retirement between 2001 & 2003 0.003 (0.4) -0.077 (-1.0) 0.267*** (3.5) R20.000.010.02

27 Conclusion Empirically, full wealth, M, and C/M match expected distribution characteristics The level of C/M has less correlation with tested circumstances than either C/NW or C/I The change in C/M is relatively invariant to recent income and employment shocks and changes in M when compared to C/NW or C/I


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