This presentation studies inequality in the US over several economics and demographics dimensions.

1. US Inequality
along numerous dimensions
Gaetan Lion, June 1, 2022

2. 2
Introduction
Objective
Studying trends in US inequality along several social dimensions including education, ethnicity, percentiles,
and work status.
We don’t explore gender because it is not disaggregated within the mentioned data that focuses on
families (fairly similar to households).
Data source
US Government Survey of Consumer Finance (SCF) data. The SCF aggregates financial data on US families
every three years. And, it discloses a time series from 1989 to 2019.
Semantics
I use the data terms, including ethnic groups, used by the SCF.

3. 3
A first measure of Inequality: Between-Difference
Between-Difference
This is the difference between two different categories.
Let’s say the median income of college graduates is $100K vs $50K for high school graduates. Here we
would measure this between-difference by observing the multiple between the two:
$100K/$50K = 2.
In other words, college graduates median income is twice the one of high school graduates. Observing this
multiple over time reveals if inequality between the two is rising or not.
Here, we focus on the median because we want to remove the noise associated with the average or the
mean when including very high income individuals & families (maybe we could call that the Elon Musk
effect).

4. 4
A second measure of Inequality: Within-Difference
Within-Difference
This is the difference within the same category.
Let’s say college graduates have a median income of $100K and a mean income of $200K. Here we would
measure this within-difference by observing the Mean/Median multiple:
$200K/$100K = 2.
In other words, college graduates average or mean income is twice the college grads median income.
Observing this multiple over time reveals if inequality within college graduates has increased or not over
time.
Contrary than for the between-difference, with the within-difference we purposefully want to capture the
Elon Musk effect since it is representative of the inequality within college graduates.
By the way, just to make sure … Elon Musk indeed graduated from college. We know it is not always true of
billionaires (Mark Zuckerberg did not).

5. 5
The mechanics of Within-Difference. Exploring the Mean/Median multiple
We start with a very simple model that splits a population into 5 different quintiles.
All quintiles have a symmetric distribution. They range from $25K to $125K in
income. They are space $25K apart. And, this population has both a median and
mean income of $75K. The resulting Mean/Median multiple is equal to 1.
Next, we sensitize the income of the 4th
and
5th
quintile in order to increase the
Mean/Median multiple.
In all cases, the median income would remain
unchanged at $75K. But, the mean income
would be the specified multiple higher.
The main point of this model is to illustrate how high the upper quintiles have to reach in order for the mean/median
multiple to reach a level of 2 to 4. As we will see this multiple level is common in the data.

6. 6
Inequalities studied
Net worth Pre-tax income Stock holdings
Overall within within within
Education between, within between, within between, within
Ethnicity between, within between, within between, within
Percentiles between, within between, within between, within
Work status between, within between, within between, within

7. 7
Definitions
Variable name Definition
Net worth Total assets minus total liabilities
Pre-tax income Wage, business and farm income, interest and dividend
income, capital gains income, social security and retirement
income, transfer and other income, rental income, pension
account withdrawals
Stock holdings Total value of equity in directly held stocks, stock mutual
funds, and combination mutual funds

8. 8
Net worth section
At times, we will compare the behavior of change in difference multiples over time with stock market
movements. I hypothesized there would be a fairly close correlation between the two (as the stock
market rises rapidly, I would have expected measures of inequality to rise too … and vice versa). But, as
we will see … at least visually (looking at time series graph), this does not appear to be the case.

9. 9
Net worth. Overall. All families
This within–difference jumped from a mean/median multiple of 4.6 in 2007 to
6.4 in 2010. Contrary to what we expected, it was not due to a rise in the
stock market that remained flat when going back to 2007 and going forward to
2010 (on an inflation adjusted basis). In between those two years, it
experienced a severe Bear market (Housing Bubble & Great Recession).

10. 10
Net Worth. Education.
College vs. High School graduates
Another between-difference that is pretty high, between
4 and 5 x since 2001. But, the rise in this between-
difference do not appear to visually correlate with stock
market movements.

11. 11
Net Worth. Education.
College graduates
This within-difference among college grads is as big as the
between-difference between college and high school grads.
This suggests that college majors and related career paths
make a huge difference in net worth accumulation.
However, again the rise in this within-difference does not
seem to correlate closely with stock market movements.

12. 12
Net Worth. Ethnicity
The between-differences between White and Black and White and Hispanic are huge. However, both
between-differences have declined markedly since their respective 1989 levels. Also, they have dropped
rapidly since 2013. Thus, even if contemporary data shows large differences. The contemporary trends
are positive as such differences are declining.

13. 13
Net Worth. Ethnicity - White
This within-difference among White is surprisingly high
and rising. Yet, again this within-difference does not
appear to be closely correlated with stock market
movement. Look at the period from 2010 to 2019, where
this within-difference remained pretty much flat around 5
x. Meanwhile, the stock market, even after adjusting for
inflation, went on a rapid Bullish run.

14. 14
Net worth. Percentiles of net worth
The between-differences between the high percentiles (75th
and 90th
) vs. the low one (25th
) are huge as can be
expected. Both those between-differences jump between 2007 and 2010, which we know was not related to stock
market movements as shown earlier.
* The table discloses the precise definition of the percentile buckets. We used the 75/25 and 90/25 difference
specification as a short cut to render some portion of the data table and the graph legend more parsimoniously
readable.

15. 15
Net worth. Percentiles of net worth, 75th
percentile
1989 1992 1995 1998 2001 2004 2007 2010 2013 2016 2019
1.1 1.1
1.1
1.0
1.0
1.0
1.0
1.1
1.1
1.1
1.1
Net Worth. 75th percentile
Mean/Median Multiple.
Here is the first difference of any kind that actually shows very little difference. Indeed, the Mean and the
Median of this 75th
percentile have remained closely aligned around a multiple close to 1 over the entire
1989 to 2019 period.

16. 16
Net worth. Percentiles of net worth, 90th
percentile
The within-difference among the 90th
percentile has remained relatively low and stable around 2 x during the entire
1989 to 2019 period. This low multiple does not signify that there could be some material differences within this
group if we looked at more granular data (remember the earlier slide ‘The Mechanics of Within-Difference’).

17. 17
Net worth. Work status
Self-Employed vs. Employee
Another pretty large between-difference that is rather expected.
Business owners accumulate more net worth capital than
employees to pretty much remain in business. However, again
the trend in this between-difference multiple does not track the
stock market.

18. 18
Net worth. Work status. Employee
This is another large and rising between-difference. But,
again it does not closely visually correlate with stock
market trend (again focus on the 2007 – 2010 period;
also look at the 2010 – 2019 period).

19. 19
Net worth. Work status.
Self-employed
Notice that this within-difference among the self-
employed is rising faster and is much larger than the
between-difference between self-employed and
employee reviewed on the prior slide. Similarly, the
rising trend in the self-employed within-difference does
not correlate closely with stock market trend (again look
at 2007 – 2010, also 1995 – 1998).

20. 20
Pre-tax income section

21. 21
Pre-tax income. Overall. All families
This is a very steady within-difference remaining within a very narrow range of 1.5 to 1.9 times since
1989. Notice how much lower this within-difference is compared to the same within-difference when
focused on Net Worth.

22. 22
Pre-tax income. Education. College vs. High School graduates
This also a rather steady between-difference around 2 x. Notice how much lower is this between-
difference than the same one focused on Net Worth. Notice that either measure of pre-tax income has not
materially changed between 1989 and 2019, on an inflation adjusted basis.

23. 23
Pre-tax income. Education. College graduates
This is another rather steady within-difference, that is also much lower than its counterpart
focused on Net Worth. Again, these measures have not increased much between 1989 and 2019
on an inflation adjusted basis.

24. 24
Pre-tax income. Ethnicity
Notice how these between-differences are so much lower than their counterparts focused on Net
Worth, reviewed earlier.

25. 25
Pre-tax income. Ethnicity - White
This is another within-difference that is relatively low and steady, and certainly much lower than its
counterpart focused on Net Worth, reviewed earlier.

26. 26
Pre-tax income. Percentiles of income
These Pre-tax income between-differences are still relatively high. But, they are a lot lower than the
same between-differences focused on Net Worth.

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Pre-tax income. Percentiles of income, 80th
percentile
1989 1992 1995 1998 2001 2004 2007 2010 2013 2016 2019
1.0
1.0
1.0
1.0
1.0
1.0 1.0 1.0
1.0
1.0
1.0
Pre-tax Income. 80th percentile
Mean/Median Multiple.
Within this percentile bucket there is pretty much no within-difference. Over the entire period, the Median and the
Mean remain very close to each other so the related Mean/Median multiple is always very close to 1 time.
Remember, that the situation was similar when looking at this same within-difference focused on Net Worth.

28. 28
Pre-tax income. Percentile of income, 90th
percentile
This is another relatively low and steady within-difference. And, it is not all that different than the
same within-difference when focused on Net Worth.

29. 29
Pre-tax income. Work status
This between-difference is surprisingly small given that its counterpart when focused on Net Worth was
so much larger.

30. 30
Pre-tax income. Work status. Employee
This is a relatively stable and low within-difference. Again, it is surprising given that the same within-
difference was so much larger when focused on Net Worth.

31. 31
Pre-tax income. Work status. Self-employed
After an abrupt drop between 1989 and 1992, this within-difference overall trend suggests a slow
increase. Notice that the self-employed pre-tax income has virtually not increased from a begin- to end-
point basis at around $75K in $2019 dollars.

32. 32
Stock holdings section
The differences, as measured, are a lot greater when focusing on Stock holdings instead of Net
Worth and Pre-tax Income.
This is an instance where we expected that long term trends in the reviewed between- and
within-differences would track stock market movements. But, for the most part we could
visually see that these differences did not track the stock market.

33. 33
Stock holdings. Overall. All families
See the steady rise in this within-difference. In 2019,
the Mean stock holdings is nearly 10 x greater than the
Median. However, the rise in this within-difference
does not correlate closely with the stock market trend.

34. 34
Stock holdings. Education.
College vs. High School graduates
This is another between-difference that does not
track the stock market (see 2007 – 2010 and 2010 to
2019).

35. 35
Stock holdings. Education.
College graduates
This within-difference trend over time has a U shape
that is completely different than the stock market
trend.

36. 36
Stock holdings. Ethnicity
1989 White/Hispanic between-difference is very much an outlier. Taking this outlier out, the trend for
both ethnicity match-ups sort of zig-zag up and down without a clear direction.

37. 37
Stock holdings. Ethnicity - White
This within-difference has really two periods. It is
rather flat from 1989 to 2013. And, then it goes on an
accelerated rise from 2013 to 2019. Yet, it often
diverges from stock market trend (see 1989 – 1998,
2007 – 2010).

38. 38
Stock holdings. Percentiles of net worth
These between-differences are huge, as expected. Notice how the 75/25 multiple has peaked in 2001.
Meanwhile, the 90/25 has kept on rising beyond its 2001 peak over the 2010 – 2019 period. These trends do
not much correspond to trends in the stock market as shown on earlier slides.

39. 39
Stock holdings. Percentiles of net worth, 75th
percentile
This within-difference has remained very steady around 1.3 to 1.4 since 1998.

40. 40
Stock holdings. Percentile of income, 90th
percentile
This within-difference has remained fairly steady since 2001 hovering within a fairly narrow range
(1.9 to 2.4).

41. 41
Stock Holdings. Work status
The self-employed own typically 3 to 4 times as much
stocks as the employees. But, this multiple has peaked
in 2001. And, again the trend in this between-
difference really does not relate much to stock market
trends.

42. 42
Pre-tax income. Work status.
Employee
This within-difference is pretty high and has risen rapidly
since 2007. But, again it does not follow the stock market
trend (see 1989 – 1998; 2007 – 2010; 2016 – 2019).

43. 43
Pre-tax income. Work status.
Self-employed
This is a very large and rising within-difference. Notice
the rise from 4.5 in 2001 to 10.1 in 2019. This
difference does not track the stock market from 1989 –
2001. But, it seems to track it reasonably from 2001 to
2019.

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Special Section: 55-64 Years Old
The 55-64 years old should have a strong balance sheet to be ready for retirement.
Given that, within this section we will focus on retirement accounts, net worth, and
financial assets.
Our focus here is not only to evaluate inequality as we have, but even more so to
evaluate retirement-readiness in terms of financial reserves.

45. 45
Additional Definition
Variable Definition
Financial assets All bank deposits, bonds, stocks, mutual funds, life
insurance cash value, managed financial assets, retirement
accounts, other financial assets (royalties, futures,
oil/gas/mineral investment, non-public stocks).
Retirement accounts IRAs, Keoghs, pensions

46. 46
55-64 years old. Retirement accounts
The current Census estimates that a 60 year old has a remaining life expectancy of 21 years. Either the
Median or Mean level of retirement funds are far from being adequate to support close to a couple of
decades in retirement. This denotes a nationwide failure in facilitating our elderly retiring somewhat
comfortably. It is unclear what is the solution given rising fiscal pressures at every level of Government.

47. 47
55-64 years old. Net worth
The Median net worth seems grossly inadequate to support a family or household into its retirement years. The
Mean net worth is more reasonable (yet probably does not make for a very comfortable and secure retirement either
for a family with a remaining life expectancy of a couple of decades). The between-difference is pronounced and
rising. And, it underlines how un-ready families at the Median level are to face decades of retirement.

48. 48
55-64 years old. Financial Assets
Similar comments as for the two previous slides. The Median financial asset level is grossly inadequate for families
nearing retirement. The between-difference is rising spectacularly fast since 2004. But, it is mainly due to the
decrease in the financial assets Median!. Meanwhile, the Mean has not materially increased since 2001 That trend is
a real concern at the nationwide level.