1. Changes in Wealth Inequality between College and High-School Graduates: Life-Cycle Model and Reality
ASSA Annual Meeting ES
January 3rd, 2010
Atlanta, GA
Takashi Yamashita
Huizenga School of Business
Nova Southeastern University

2. Objective of This Research
In this paper, I document what happened to the gap of wealth holdings between households headed by college graduates vs. high-school graduates, using nationally-representative sample of the U.S. household wealth data.
Data description and a fact-finding study

3. Motivation
Earnings and income inequality widened in the United States in the past 30 years in various dimensions.
Research on consumption inequality has produced mixed results:
Consumption inequality did not increase much (Slesnick 2001, Krueger & Perri, 2006, Meyer and Sullivan, 2009)
Consumption inequality widened more than income inequality (Attanasio & Davis 1996, Attanasio et al. 2004)
What happened to wealth inequality?

4. Changes in Earnings Inequality, 1963-2005

5. Why is This Question Important?
Wealth links the past and present to the future.
Have certain segments of the population become more vulnerable to economic shocks?
Different patterns of wealth holdings may indicate imperfections in the asset markets.
Are some households participation-constrained?
An increase in inequality has implications for asset pricing (Gollier 2001).
Could we expect a higher equity premium?

6. Approach
Compare the median wealth of college graduates to that of high-school graduates.
Consider whether the life-cycle model is consistent with the observed wealth gap.
Decompose the wealth gap and examine how the contribution of each component has changed.
Compare portfolio holdings of the two groups and see how the differences in portfolios resulted in wealth inequality.

7. Contributions of the Paper
Provides an overview of the wealth gap by educational attainment.
This dimension of wealth inequality has not been a focus of previous research.
Dynamics of the wealth gap by education appear different from those of other dimensions of inequality.
My results highlight the importance of risky assets and owner-occupied housing in wealth portfolios.

8. Data I use the Survey of Consumer Finances (SCF) from 1989 to 2007.
It’s a detailed survey of household balance sheets conducted by the Federal Reserve every three years.
It oversamples high-income households:
Suitable for analyzing assets disproportionately held by wealthy households, such as stocks and business interests.
I limit my samples to:
High-school graduates (exactly 12 years of schooling with a diploma, incl. a GED) and college graduates (16+ years of schooling and with a bachelor’s degree) between age 24 and 59.
In the labor force at the time of the survey.

9. Caveats of the SCF
Income process over the sample period may not reflect what’s observed in the CPS.

10. Box Plot of Net Worth by Education

11. Wealth Gap by Education (Levels)

12. Wealth Gap vs. Life-Cycle Hypothesis
The observed wealth gap by education cannot be accounted for by a simple life-cycle hypothesis.
Assuming that the income gap reflects the differential in permanent income, with reasonable assumptions of work years and longevity differences between the two groups, we can calculate how the income gap would translate into the wealth gap under a life-cycle model.
High-school graduates work from 18 to 65, die at 72
College graduates work from 24 to 62, die at 78

13. Wealth Gap vs. Life-Cycle Hypothesis
1989
1992
1995
1998
2001
2004
2007
College/HS income gap median)
1.69
1.66
1.64
1.78
1.98
1.95
1.86
Life-cycle wealth gap
2.85
2.80
2.76
3.01
3.34
3.29
3.14
Actual wealth gap
median)
3.44
2.97
2.18
3.80
4.36
3.99
4.39
The observed wealth gap fluctuates too much to be explained by the income gap

14. Wealth Gap vs. Life-Cycle Hypothesis
Improvement of longevity among college graduates (from 78 to in 2007)
1989
1992
1995
1998
2001
2004
2007
College/HS income gap median)
1.69
1.66
1.64
1.78
1.98
1.95
1.86
Life-cycle wealth gap
2.85
2.86
2.90
3.22
3.66
3.67
3.57
Actual wealth gap
median)
3.44
2.97
2.18
3.80
4.36
3.99
4.39

15. Wealth Gap vs. Life-Cycle Hypothesis
Introduction of Social Security with the replacement ratio of 0.7 for high-school graduates and 0.6 for college graduates
1989
1992
1995
1998
2001
2004
2007
College/HS income gap median)
1.69
1.66
1.64
1.78
1.98
1.95
1.86
Life-cycle wealth gap
3.81
3.61
3.51
4.33
5.44
5.26
4.75
Actual wealth gap
median)
3.44
2.97
2.18
3.80
4.36
3.99
4.39

16. Look at the Conditional Distribution
We have looked at differentials of the unconditional mean and median wealth.
However, the compositions of the samples change across years.
Conditional Distribution
I look at the changes in the coefficient estimates from quantile regressions from 5- to 95-percentile
Regressions control for age (13 dummies), education, race, marital status, female headship, attitudes towards risk, planning horizon, attitudes toward saving, and log of labor income.

17. Coefficients from Quantile Regressions

32. Evolution of within-group variance of log wage of men by education (Figure 2A. Lemieux, AER 2006)

33. Decomposition Analysis
I decompose the change in wealth dispersion into: the change in characteristics, the change in relationships between such characteristics and wealth level (i.e., regression coefficients), and the change in residual dispersion.
In the OLS framework, Juhn-Murphy-Pierce extend the Oaxaca-Blinder decomposition to the entire distribution (JMP, 1991, 1992).
Melly (2005, 2006) and Autor-Katz-Kearney (2006) extend the JMP decomposition to the quantile regression framework.

34. Decomposition Analysis
Total college-high-school differentials at selected percentiles are decomposed into differences in:
the college wealth and the counterfactual wealth if the median coefficient of high-school graduates were the same as college graduates’ but the residuals were distributed as in the high-school graduates’ distribution;
the counterfactual of high-school graduates in (a) and the counterfactual wealth had college graduates experienced the same coefficient as high-school graduates, and
the counterfactual of college graduates in (b) and the high-school wealth

35. Decomposition Analysis

36. What does decomposition tell us?
Level of the Wealth Gap
At the low and middle levels of wealth, large part of the wealth gap is accounted for by characteristic differentials.
Only at the very top of the wealth distribution, the role of characteristics becomes smaller.
Changes in the Wealth Gap
The role of characteristic differences increased its importance, as the statistical association between characteristics and the wealth level weakens.
At the lower wealth level, the decline in the wealth gap coincide with the decline in residual dispersion.
At the higher wealth, the part explained by residual dispersion increased considerably.

37. What are the Differences in Characteristics?
‘89
‘92
‘95
‘98
‘01
‘04
‘07
Age High School
39.5
39.0
40.0
40.5
40.4
41.0
College
39.8
403
41.4
42.2
42.5
Black HS
10.6
14.1
16.2
15.5
17.4
15.2
15.0
6.2
8.1
7.1
7.2
9.5
8.9
Other Race HS
13.8
13.3
8.3
9.7
11.3
14.5
14.7
7.8
7.0
8.7
10.1
13.7
Married HS
65.5
66.8
69.2
62.5
64.1
63.6
68.7
69.0
66.9
65.4
65.8
70.7
68.0
68.4
Divorced HS
20.4
19.2
16.9
23.0
21.4
20.1
17.5
13.1
16.1
12.4
13.0
14.3
Widowed HS
2.8
1.1
1.3
2.3
1.9
3.5
1.5
1.2
1.0
1.7
0.9
Fem Head HS
23.9
21.3
20.8
22.1
22.4
20.0
14.6
17.6
21.0
19.6
18.2
19.4
18.3

38. Most important time period in planning saving
‘89
‘92
‘95
‘98
‘01
‘04
‘07
Few Months
High School
22.9
21.2
21.9
25.1
16.3
19.9
23.1
College
18.2
16.5
12.2
12.5
10.5
11.2
11.0
Next Year
12.9
13.4
16.9
16.4
12.7
10.8
10.6
8.2
8.9
7.5
Few Years
25.8
27.8
13.9
25.7
27.5
27.3
27.7
24.1
23.7
15.6
26.8
23.5
24.6
26.7
5~10 years
24.7
35.7
21.5
26.5
26.3
20.7
26.1
35.1
26.6
28.6
32.3
30.2
> 10 Years
13.7
15.7
11.6
14.2
12.6
10.2
20.8
29.2

39. Which describes your saving habits?
‘89
‘92
‘95
‘98
‘01
‘04
‘07
Spend more than or as much as income, or no regular saving plan
High School
58.5
57.0
59.0
58.1
56.9
54.9
58.9
College
40.9
41.8
35.9
35.3
34.8
32.3
Save income of one family member or save regularly
42.7
44.0
42.4
42.9
44.1
46.5
41.3
62.2
59.3
59.6
65.4
66.8
66.7
70.0

40. How much financial risk are you willing to take?
‘89
‘92
‘95
‘98
‘01
‘04
‘07
Substantial risks for substantial returns
High School
5.3
3.3
3.4
4.4
3.9
3.2
College
3.8
5.8
7.8
6.7
4.0
5.4
Above-average risks for above-average returns
7.9
8.7
11.2
16.0
14.2
13.7
12.5
15.6
22.1
26.6
35.7
26.9
29.9
33.6
Average risks for average returns
39.6
37.3
37.6
39.7
39.3
37.0
38.8
56.6
50.8
48.2
43.7
41.7
48.1
48.3
Not willing to take any financial risks
47.3
50.7
47.8
39.1
42.0
45.4
45.6
24.0
23.8
19.4
12.8
14.7
18.0
12.7

41. Household Characteristics and Portfolio Composition
The differences in household characteristics are manifested in portfolio holdings of the two groups.
High-school graduates have
lower level of wealth,
safer portfolios (less in risky assets),
but hold more in illiquid assets.
College graduates have
higher level of wealth,
riskier portfolios,
and higher debt (mostly mortgages).

42. Some Portfolio Statistics*
‘89
‘92
‘95
‘98
‘01
‘04
‘07
Net Worth
High School
$52,838
$44,526
$68,743
$58,554
$70,978
$58,791
$62,636
College
$178,520
$132,233
$149,923
$222,552
$308,984
$237,746
$274,690
% own home
57.3
56.4
59.3
60.1
60.7
59.6
64.9
70.8
67.7
67.2
70.1
77.2
80.0
78.5
House $ HS
$112,692
$96,375
$108,150
$108,220
$111,112
$142,776
$175,000
$193,186
$173,648
$182,503
$197,343
$210,527
$274,570
$300,000
Mortgage HS
$32,198
$37,624
$47,315
$50,927
$53,801
$76,880
$84,000
$78,884
$86,824
$97,335
$103,128
$106,433
$139,481
$148,000
% own stocks
24.9
27.7
34.0
42.9
45.9
45.8
43.5
53.2
56.2
63.1
72.0
77.3
76.2
79.7
Med. F/NF HS
0.151
0.154
0.152
0.203
0.246
0.126
0.124
0.331
0.335
0.481
0.696
0.687
0.322
0.349
*In constant 2007 dollars, $values at median

43. Differentials in Asset Holdings

44. Differentials in Debt Holdings

45. Differentials in Housing and Non-Housing Wealth

46. High-school graduates have become highly leveraged
‘89
‘92
‘95
‘98
‘01
‘04
‘07
CC Bal/Liquid Asset
High School
0.050
0.140
0.210
0.131
0.116
0.186
0.159
College
0.028
0.020
0.045
0.011
0.000
0.004
0.017
% LTV > 0.8
8.6
15.3
20.8
24.4
19.7
21.5
21.6
13.4
18.4
22.6
18.9
14.3
18.5
18.7
Med. LTV Ratio
0.298
0.442
0.449
0.496
0.500
0.550
0.525
0.497
0.520
0.587
0.571
0.521
0.553
0.507
House $/Net Worth
0.926
1.010
0.866
0.817
0.810
1.109
1.159
0.792
0.777
0.811
0.562
0.532
0.868
0.813

47. Conclusions
The wealth gap between college and high-school graduates initially narrowed and then widened in the sample period.
The pattern of the wealth gap matches that of the household income gap.
The gap in the wealth-to-income ratio also exhibits a similar pattern.
However, the life-cycle accumulation motive alone cannot account for the wide year-to-year fluctuations in wealth gap.
The life-cycle model cannot capture the wide swings of the wealth gap between the two groups.
The increase in within-group inequality seems to coincide with the growth of within-group inequality in wages.

48. Conclusions
The majority of the differences in the wealth level can be explained by the differences in household characteristics.
However, even after controlling for the household characteristics, the estimates on education dummy declined from 1989 to 1995 and then widened.
The changes in wealth inequality are largely due to changes in residual dispersion (i.e., luck?).
By 2004, poor college households have become much poorer than their poor high-school counterpart, and rich college graduates are much wealthier than their high-school counterpart.

49. Conclusions
The characteristics differences of the two groups are reflected in divergent portfolio holdings.
Wealth accumulation for low-income, less-educated households is closely tied to homeownership.
Housing policy to promote homeownership is important in “spreading the wealth around.”
However, housing could be a double-edged sword.

50. Future Directions Is the SCF representative?
Compare with the CPS to see if demographics of the SCF samples are representative
This study can be easily extended to the other dimensions:
Overall Inequality
Black-White wealth gap
Cohort differences in wealth accumulation patterns