1. Changes in Wealth Inequality between College and High-School Graduates Far East and South Asia Meeting of the Econometric Society August 4, 2009 Tokyo, Japan 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 (Slesnick 2001, Krueger & Perri, 2006) –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. Decompose the wealth gap and examine how the contribution of each component has changed. Examine 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. Summary of Key Findings The College-High-School gap first narrowed (~’95) and then widened (after ‘95). –Narrowing of the homeownership gap contributed to the earlier compression. –After 1995, the homeownership of the two groups diverges, thus the wealth gap widened. –The stock-market boom of 1996-2001 aggravated the wealth gap. –The housing-market boom of 2001-2007 further increased the wealth gap, as college graduates bought bigger, more expensive houses.

9. 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: 1.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. 2.In the labor force at the time of the survey.

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

11. Variable Transformation Wealth variables are strongly right-skewed. –Logarithmic transformation could make the distribution closer to symmetric. Wealth, however, may take zero or negative values. When convenient, I use the following transformation to analyze the wealth variables.

12. Box Plot of Net Worth by Education

13. Wealth Gap by Education (Levels)

14. Wealth Gap by Education (Ratios)

15. Summary of Net Worth Differentials Both at the mean and median, the college-high- school wealth gap narrowed in the early 1990’s but started to widen after 1995. The gap was biggest in 2001 and then slightly contracted in 2004, but again widened in 2007. Capital gains (gains in both financial assets and housing) and inheritances seem to moderate the C/HS wealth gap. –They are a minor part in the wealth gap, at least at the median. College households have much wider dispersion of overall wealth compared to high-school households, and their spread has become bigger.

16. 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 75 College graduates work from 25 to 65, die at 85

17. Wealth Gap vs. Life-Cycle Hypothesis These numbers could change by changing assumptions, but the predicted life-cycle wealth gap does not fluctuate much given the income gap. 1989199219951998200120042007 College/HS income gap (@ median) 1.691.661.641.781.981.951.86 Life-cycle wealth gap 2.192.152.122.312.572.522.42 Actual wealth gap (@ median) 3.442.972.183.804.363.994.39

18. 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.

19. Coefficients from Quantile Regressions

34. Change in Residual Variance for Male Workers in CPS (Lemieux AER 2006)

41. 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.

42. Decomposition Analysis Total college-high-school differentials at selected percentiles are decomposed into differences in: 1.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; 2.the counterfactual of high-school graduates in (a) and the counterfactual wealth had college graduates experienced the same coefficient as high-school graduates, and 3.the counterfactual of college graduates in (b) and the high-school wealth

43. Decomposition Analysis

44. 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.

45. What are the Differences in Characteristics? ‘89‘92‘95‘98‘01‘04‘07 Age High School 39.539.040.040.540.441.040.4 College 39.840340.041.442.242.541.4 Black HS 10.614.116.215.517.415.215.0 College 6.28.17.17.27.19.58.9 Other Race HS 13.813.38.39.711.314.514.7 College7.87.08.17.88.710.113.7 Married HS 65.566.869.262.564.163.668.7 College69.066.965.465.870.768.068.4 Divorced HS 20.419.216.923.021.420.117.5 College13.713.116.113.712.413.014.3 Widowed HS 2.81.11.32.31.93.51.5 College1.21.01.71.21.11.00.9 Fem Head HS 23.921.320.822.122.4 20.0 College14.617.621.019.618.219.418.3

46. Most important time period in planning saving ‘89‘92‘95‘98‘01‘04‘07 Few Months High School 22.921.221.925.116.319.923.1 College 18.216.512.212.510.511.211.0 Next Year High School 12.913.416.913.4 16.412.7 College 16.310.816.310.68.28.97.5 Few Years High School 25.827.813.925.727.527.327.7 College 24.123.715.626.823.524.626.7 5~10 years High School24.721.935.721.526.523.726.3 College20.726.135.126.628.632.330.2 > 10 Years High School13.715.711.614.216.412.610.2 College20.822.920.723.529.223.524.6

47. 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 58.557.059.058.156.954.958.9 College 40.9 41.835.935.334.832.3 Save income of one family member or save regularly High School 42.744.042.442.944.146.541.3 College 62.259.359.665.466.866.770.0

48. How much financial risk are you willing to take? ‘89‘92‘95‘98‘01‘04‘07 Substantial risks for substantial returns High School 5.33.33.45.34.43.93.2 College 3.83.35.87.86.74.05.4 Above-average risks for above-average returns High School 7.98.711.216.014.213.712.5 College 15.622.126.635.726.929.933.6 Average risks for average returns High School 39.637.337.639.739.337.038.8 College 56.650.848.243.741.748.148.3 Not willing to take any financial risks High School47.350.747.839.142.045.445.6 College24.023.819.412.814.718.012.7

49. 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).

50. 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 High School57.356.459.360.160.759.664.9 College 70.867.767.270.177.280.078.5 House $ HS $112,692$96,375$108,150$108,220$111,112$142,776$175,000 College $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 College $78,884$86,824$97,335$103,128$106,433$139,481$148,000 % own stocks High School24.927.734.042.945.945.843.5 College 53.256.263.172.077.376.279.7 Med. F/NF HS 0.1510.1540.1520.2030.2460.1260.124 College 0.3310.3350.4810.6960.6870.3220.349 *In constant 2007 dollars, $values at median

51. Differentials in Asset Holdings

52. Differentials in Debt Holdings

53. Differentials in Housing and Non-Housing Wealth

54. Main Findings The increase in housing wealth of high-school graduates from 1989 to 1995 coincides with the narrowing of the net-worth gap. The rise of stock holdings and housing wealth of college graduates coincide with the widening of the net-worth gap after 1995. The wealth gap in 2004 would have been much smaller had we excluded housing as college graduates shifted from financial assets to housing. Then high-school graduates started investing heavily in housing from 2004 to 2007.

55. High-school graduates have become highly leveraged ‘89‘92‘95‘98‘01‘04‘07 CC Bal/Liquid Asset High School 0.0500.1400.2100.1310.1160.1860.159 College 0.0280.0200.0450.0110.0000.0040.017 % LTV > 0.8 High School 8.615.320.824.419.721.521.6 College 13.418.422.618.914.318.518.7 Med. LTV Ratio High School 0.2980.4420.4490.4960.5000.5500.525 College 0.4970.5200.5870.5710.5210.5530.507 House $/Net Worth High School 0.9261.0100.8660.8170.8101.1091.159 College 0.7920.7770.8110.5620.5320.8680.813

56. Net Worth to Income Ratio

57. Selected Assets to Income Ratio

58. Selected Debt Items to Income Ratio

59. Housing and NH Wealth to Income Ratio

60. 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 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.

61. 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. –We should also consider a general-equilibrium effect of promoting homeownership.

62. Future Directions What happened after the housing-market collapse? –The 2007 SCF has not captured the collapse of the housing market. This study can be easily extended to the other dimensions: –Overall Inequality –Black-White wealth gap –Cohort differences in wealth accumulation patterns