Top Wealth in America: New Estimates and Implications for Taxing the Rich
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The top 0.1% share of wealth in the US increased from 12.9% to 15% btw 2001-2016, according to @MatthewSmith @nberpubs.
Research from Matthew Smith, Owen Zidar and Eric Zwick uses administrative tax to estimate wealth concentration/composition for the US. Their bottom line, “…the top 0.1% share of wealth has increased from 12.9% to 15% from 2001 to 2016. While this increase is lower than some prior estimates, wealth is very concentrated – the top 1% holds nearly as much wealth as either the bottom 90% or the P90-99″ class. We find that pass-through business and public equity wealth are the primary sources of wealth at the top, and pension and housing wealth account for almost all wealth for the bottom 90%….”
Core of paper, “…This paper uses administrative tax data to estimate top wealth in the United States. We assemble new data that links people to their sources of capital income and develop new methods to estimate the degree of return heterogeneity within asset classes. We combine this Data on fixed income and pass-through business returns with refined estimates of C corporation equity, housing, and pension wealth to deliver new capitalized wealth estimates. Our approach which builds on SZ and Piketty, Saez and Zucman (2018) (PSZ) as well as Bricker, Henriques and Hansen (2018) (BHH)|reduces bias because wealth and rates of return are correlated. We provide new wealth estimates, new evidence on the rates of return, and a systematic analysis of the issues most consequential for capitalization. We find less wealth concentration relative to the equal-returns, individual-level approach in PSZ, especially at the very top. Figure 1A shows that the top 0.1% wealth share in 2016 is 15% under our approach, and around 20% in PSZ. Top 1% and 0.01% shares fall by 24 percent and 36 percent, respectively, leaving the recent wealth estimates above the estate tax series and closer to the SCF. The growth in top wealth shares is also less dramatic, especially in the tail. For example, our approach reduces the growth in top 0.01% shares since 1989 by 45%. Nevertheless, wealth is very concentrated:the top 1% holds nearly as much wealth as either the bottom 90% or the P90-99″ class. In terms of top portfolios, we find a larger role for pass-through business wealth and a much smaller role for fixed income wealth than PSZ, consistent with the composition of top wealth in the SCF, estate tax data, and surveys of family offices of the ultrarich. Passthrough business and C-corporation equity wealth are the primary sources of wealth at the top. At the very top, C-corporation equity is the largest component, accounting for 40% of top 0.01% wealth, but pass-through business looms large at 29%. In contrast, pension and housing wealth account for almost all wealth of the bottom 90%…”
The Level of Top Wealth, “… Table 2 shows the number of individuals in each wealth group and the wealth thresholds defining each group. We then report average wealth and the share of total wealth for these groups when applying the equal-returns approach and ranking of PSZ. Panel A focuses on top wealth groups. The full population includes 239 million individuals whose average wealth is $364K in 2016. The top 1% includes 2.4 million individuals with wealth of at least $3.7M and average wealth equal to 32 times average wealth in the full population. In terms of shares, this group’s share of total wealth is 31.5% under our preferred approach, compared to 36.6% under PSZ equal returns. Similarly, for the top 0.1%, who have wealth exceeding $17.8M, our estimates reduce their share from 18.6% under equal returns to 15.0% in our preferred specification. Thus, the combined effect of accounting for estimated heterogeneity, updating Financial Accounts aggregates, estimating private business values, adding Forbes 400 data, and including unfunded pension wealth materially affects the estimated concentration of top wealth. These adjustments are increasingly important within the very top group, as the top 1% share falls by 14% (5:1=36:6), the top 0.1% share falls by 19% (3:6=18:6), and the top 0.01% share falls by 26% (2:5=9:5). Panel B focuses on intermediate wealth groups. A key result is that the bottom 90%, who collectively hold 34.3% of wealth, are allocated 5.6 p.p. more wealth than in PSZ. The P90-99″ class, a group with more than $717K but less than $3.73M in preferred wealth, hold 34.2% of total wealth, on par with the bottom 90% and more than the top 1%. Figure 11 compares Forbes 400 wealth to aggregate wealth according to our preferred specification for telescoping subgroups of the top 1%: P99-99.9, P99.9-99.99, and the top 0.01%. We report totals and counts of individuals in each group as well as results using tax units. The wealth threshold to be in the top 0.01% in 2016 is $84M for individuals and $124M for tax units. The figure provides perspective on the relative importance of accounting for Forbes wealth if capitalization alone misses their unrealized stock wealth in non-dividend-paying companies. The Forbes 400 have considerable wealth ($2.4T in 2016), but the total wealth of the P99-99.9 and P99.9-99.99 tax unit groups exceeds this amount by factors of 6.2 and 3.0, respectively. Of course, Forbes members are much wealthier on average: these groups respectively contain 1.5 million and 150 thousand tax units, whereas Forbes represents only 400. Our top 0.01% group contains $6.6T of wealth, which includes the impact of blending Forbes into our data…”

Matthew Smith, Owen Zidar and Eric Zwick, “Top Wealth in America: New Estimates and Implications for Taxing the Rich,” National Bureau Of Economic Research, October 2021, https://www.nber.org/papers/w29374
Individual-Level Rates of Return, “… Figure 4B presents fixed income rates of return for 2016.We calculate rates of return as the group-level ratio of total interest income divided by total interest-generating fixed income assets. We plot these returns ranking individuals by our estimate of total wealth. Rates of return increase from 0.80% for P0-90 to 0.77% for P90-99 to 0.89% for P99-99.9 to 1.65% for P99.9-99.99 to 3.43% for P99.99-100. Rates of return that rank by AGI or by non-interest wealth display moderately greater heterogeneity in absolute terms though the differences are similar in relative terms. Overall, these data reveal a striking amount of return heterogeneity with the P99.99-100 wealth groups receiving returns that are 3.3 times average returns. At the same time, top rates of return are considerably below the top boutique rates, which reflects the mix of high- and low-yielding fixed income assets held by
those at the top of the wealth distribution…”

“… Figure 4C shows the time series of top 0.01%, top 0.1%, top 1%, and bottom 99% rates of return ranked by our preferred wealth estimates. We compare these rates to the equal returns rate and to various capital market rates: the deposit rate from Savov, the 10-year US Treasury rate, and the Moody’s Aaa and Baa corporate bond rates. All interest rates reached a peak in the 1980s during the Volcker tightening and have been falling since then. In the years since 2000, the bottom-99% rate tracks the deposit rate closely, exceeding it by approximately 0.8% in the low-interest-rate period. The equal-returns yield, which fell from 9.5% in 1982 to 1.1% in 2016, exceeds the bottom-99% but is below the top-1% and top 0.1% rates. The top-1% rate tracks the 10-year US Treasury rate although is slightly lower since the Great Recession. The top-0.1% rate hovers between the 10-year US Treasury and the Aaa rate, moving toward the 10-year rate in the last few years of the sample. In our series, top-0.01% rate is below the riskier Baa corporate bond rate in almost all years and is slightly below the Aaa rate in 2016….”
Note they ~ mirror Sarin’s findings on the impact of social security“…For pension wealth, we capitalize an age-group specific combination of wages and pension distributions. This approach allows us to incorporate the life-cycle patterns in pension wealth and associated income flows. While less important for top wealth,pension wealth accounts for 63% of wealth for the bottom 90% and 36% for the P90-99 group. Although we do not account for the value of Social Security in our main specification, we show that doing so would further increase the role of this category of wealth and flatten the trend in measured wealth concentration….The life-cycle of pension wealth accumulation further complicates the capitalization approach. Figure 9A uses the SCF to plot average wages, pension income, and pension wealth in 2016 dollars, averaging across cohorts from 1989 to 2016. Wage income grows over the life cycle and then declines starting around age 55 to near zero by age 75. In contrast, pension income is nearly zero until age 60. Pension wealth has an inverse-U shape that reflects the accumulation and decumulation of savings. These life cycle dynamics result in flow-to-stock ratios that vary by age. Figure 9B summarizes this heterogeneity by plotting the ratio of wage and pension income to total pension wealth, respectively. The blue bars depict the population average and the red bars show the ratios for four age groups: below 45, 45 to 59, 60 to 74, and above 75. Wage income of adults younger than 45 amounts to 108% of their pension wealth on average, whereas average wages for those above age 75 are only 3% of their pension wealth. The patterns for pension income are reversed. The ratios for those between 45 and 74 are closer to the population averages in blue, with the 45 to 59 aged group having a wage to pension wealth ratio that is similar to the overall average, while those aged 60 to 74 have smaller wage to pension wealth ratios, reflecting larger retirement rates. Overall, the heterogeneity in pension wealth and ow-to-stock ratios across age groups means that an age-group-invariant approach will induce large errors…”

Level and composition of aggregate Wealth. “… Figure 2A decomposes aggregate wealth and plots the evolution of key components relative to national income.Other than pass-through business, each component is from the Financial Accounts. In 2016, national wealth amounts to 540% of national income. The largest component is pensions, which equals 203% of national income (of which 40 p.p. are unfunded defined benefit pensions).8 Housing net of mortgages is the next largest (117%), followed by fixed income assets (94%), pass-through business which includes proprietorship, partnership, and S-corporation equity (71%)|and C-corporation equity (67%). Combined C-corporation and pass-through business wealth gives 138%, fifty percent more than the amount of fixed income wealth and commensurate with funded pension wealth. Non-mortgage debt, which includes credit-card balances, debt secured by durable goods, student loans, and other loans, amounts to -16% of national wealth. Aggregate wealth is 77 percentage points of national income higher than in PSZ, of which 40 p.p., 15 p.p., 10 p.p., and 12 p.p. are from unfunded defined benefit pensions, our bottom-up pass-through estimates, adjustments to non-mortgage debt, and residual updates. At the aggregate level, wealth has increased from 346% in 1966 to 540% of national income. Of that increase, 124 percentage points are from pensions, 38 are from net housing, 22 from pass-through business, 18 are from fixed income, and -7 from C-corporation equity.

Level and composition of observed capital income.. “…. Figure 2B plots six types of capital income relative to national income from 1966 to 2016. Aggregate interest income of U.S. individuals increased in the late 1970s and boomed in the early 1980s. It then fell in the 1990s back to its initial share of national income. Since 2000, aggregate interest income has been falling and amounted to 0.6% of national income or $102 billion in 2016. Pension and pass-through income are now the largest sources of capital income. Pension income has risen tenfold from 0.7% to 6% of national income from 1966 to 2016.Pass-through income was 6.8% in 1966, fell to 4% in the early 1980s, and then recovered following the Tax Reform Act of 1986 to 7.3% in 2016. Aggregate dividend income of U.S. individuals amounts to 1.6% and has fluctuated mildly around that level over this period. In contrast, aggregate capital gains of U.S. individuals is much more volatile and ranges from 2% to over 8%. Aggregate property tax payments, which are capitalized to estimate housing assets, amount to approximately 1.2% and grew modestly during the 2000s housing cycle….”
Good factoid, “…Therefore, a dollar of interest income for a wealthy person corresponds to a different level of assets than for a poorer person. Figure 3A uses the 2016 SCF to decompose fixed income holdings into two broad categories: liquid assets, including currency, deposits, and money market funds; and less liquid assets, including bonds, non-money-market fixed income mutual funds, and other fixed income assets. Among fixed income assets, high net worth households have more of their fixed income assets in bonds and other securities. The top 0.1% hold less than 20% of their fixed income portfolio in liquid assets. Bonds and xed income mutual funds account for over 80%. In contrast, the bottom 90% hold more than 80% of their fixed income assets in liquid assets…”
Top wealth overtime, “…. Figure 1 plots our preferred estimates from 1966 to 2016 for the top 0.01%, top 0.1%, and the top 1%. For the top 0.1%, top wealth falls from 10% in the late 1960s to a low of 5.7% in 1978, then steadily rises to around 15% in recent years. Relative to the PSZ series, our preferred series not only shows a lower level in recent years but less growth since 1980. The PSZ top 0.1% series grew from 6.3% in 1978 to 18.6% in 2016; our preferred series grew from 5.7% to 15.0%. Focusing on the 1989-2016 period during which the SCF is available, the top 0.1% share grew 5.1% in our series, 4.3% in the SCF, and 8.1% in PSZ. The gap between the PSZ and preferred series is even larger in recent years for the top 0.01%. Our series and the PSZ series track each other closely before 2000, but they diverge in 2000, especially since 2007. In our series, the top-0.01% shares increase from 5.8% in 2001 to 6.2% in 2006 to 7.0% in 2016; in the PSZ series, the increase from 2001 to 2006 is similar but the increase from 2006 to 2016 is three times larger. For both of these top groups, our series closely tracks the harmonized SCF with Forbes in recent years. For the top 1%, we find a similar trend to the harmonized SCF with Forbes but a lower level. Since 2000, the SCF top 1% share is between the equal-returns series and our preferred series, though shows a sharper increase between 2013 and 2016 that appears to have partly reversed in the 2019 survey. Figure 13 plots time series versions of Figure 12 for the major asset classes for the top 0.01%, top 0.1%, and top 1% in our series, the PSZ equal-returns series, and the harmonized SCF. The figure helps provide a more systematic presentation of the composition of top wealth over time relative to the equal-returns approach. The figure also displays when different updates occur (1980s for pension and housing, 2001 for pass-through and fixed income with information-returns) and the corresponding effects, and how policy and macroeconomic conditions affect the concentration and composition of wealth. For the top 1%, we include estimates from the DFA for comparison…”

Composition of top wealth, “…Tables 3A and 3B show the wealth composition in 2016 for each wealth group in our preferred approach. Pass-through business, C-corporation equity, and fixed income account for 26%, 32%, and 23% of top 0.1% wealth, respectively, with the rest in housing and pensions. At the very top, C-corporation equity is the largest component, accounting for 40% of top 0.01% wealth, but pass-through business looms large at 29%. In contrast, the wealth composition for the bottom 90% is 63% pensions and 23% in housing. The portfolios of the P90-99 are more balanced, with almost equal shares from fixed income (18%), C-corporation plus pass-through equity (21%), housing (25%), and a larger role for pensions (36%). Figure 12 plots the level and allocation of wealth across asset classes among the top 10%. We group individuals into percentile bins and further divide the top 1% into P99- 99.9, P99.9-99.99, and the top 0.01%. Each plot shows the share of total household wealth accruing to that group in a particular asset class. We compare our preferred estimates to the PSZ equal-returns approach and the harmonized SCF with Forbes. The figure displays where in the distribution and across assets differences in approach lead to differences in top wealth shares. Overall, the top 0.01% has 7.0% of total household wealth in our series, of which 1.3 p.p., 2.0 p.p., 2.8 p.p., and 0.9 p.p. are due to fixed income, pass-through business, public equity, and other categories, respectively. The largest difference between our series and the PSZ series is fixed income, for which the PSZ approach estimates fixed income assets of the top 0.01% account for 4.1% of total US household wealth. This difference is partially o set by our pass-through business estimate, which exceeds PSZ’s estimate of 1.1% of total household wealth by 0.9 percentage points. The estimates for the other asset classes are similar for the top 0.01%. In our series, those in the P99-99.9 hold a substantial amount of wealth that exceeds that held by the top 0.1% in terms of fixed income and have considerably more wealth in pensions and housing. For pass-through wealth, the P99-99.9 hold 2.9% of total household wealth, whereas the top 0.1% holds 3.9%. C-corporation equity is more concentrated, as the top 0.01% holds more wealth than the P99-99.9 and P99.9-99.99 groups despite representing 1/100th and 1/10th the number of individuals, respectively…”

“… Figure 14A plots top 1%, P90-99, and P0-90 wealth shares over this time period under both our preferred and the equal-return approaches. The difference in growth between the PSZ and preferred approaches is less pronounced for the top 1% than for the top 0.1% and top 0.01%, with the growth of the top 1% share from 2001 to 2016 falling from 5.4 to 4.2. percentage points. Overall, wealth is still concentrated: the top 1% holds nearly as much wealth as either the bottom 90% or the P90-99″ class. The evolution of the P0-90 versus P90-99 shares from 1965 to 2000 reflects the evolution of pensions, housing, and public equity and relative exposures for different groups. Aggregate pension wealth rises secularly over this time, which is most important for the bottom group. Housing wealth rises and falls in the 1980s, affecting the bottom group and the P90-99 groups significantly. Public equity wealth falls in the 1970s, remains low, and then resurges in the mid-1990s, which drives the time series for the top 1%. In more recent years, the bottom 90 group loses ground relative to both the top 1% and the P90-99. These results are consistent with findings from other data sets (e.g., Kuhn, Schularick, and Steins (2020)). Saez and Zucman (2016) also highlight the decline of P0-90 wealth driven by housing and an increase in debt. Our series shows a less dramatic decline due to the increased role for pensions, including unfunded defined benefit plans, smaller aggregate non-mortgage debt, as well as the more concentrated nature of housing wealth in our unequal-property-tax-rate series. Average wealth of the bottom 90 increased modestly by 17% from 2001 to 2016 (from $120K to $140K in 2016 dollars), whereas average wealth for P90-99 and the top 1% rose by 40% and 49% (from $1.0M to $1.4M and from $7.7M to $11.5M), respectively…”

The rich are able to get better returns, “…We introduce two innovations to estimate fixed income wealth. First, we construct a novel data set on the universe of taxable interest sources linked to owners using de-identified ed data from income tax records spanning 2001-2016. These 3.2 billion source-owner observations allow us to disaggregate taxable interest income into subcomponents. This disaggregation reveals that rich individuals earn a much larger share of their interest income in the tax data in higher-yielding forms (such as boutique investment partnerships of distressed debt or mezzanine funds). Disaggregation also allows us to estimate interest rates more accurately than prior work. These data reveal a striking amount of return heterogeneity across wealth groups, with the top 0.01% group receiving returns that are 3.3 times average returns. In 2016, our estimates increase from nearly 1% within the bottom 99.9 to 1.6% for P99.9-99.99 to 3.4% for the top 0.01%…“


