Political Calculations
Unexpectedly Intriguing!
October 22, 2019

Net wealth is looking like it will be a hot topic in the upcoming 2020 election season in the United States, with several candidates proposing to tax high net worth households to only partially pay for the explosion in federal government spending they are also proposing.

How at risk are you might be to these newly proposed taxes on wealth depends on what your household's net worth is and how your rank in net worth among all Americans. To help answer the first part of that question, we'll direct you to Bankrate's Net Worth Calculator, which will add up the value of your assets and subtract out your liabilities to estimate your household's net worth, assuming you haven't already done that math.

After you have that figure, plug it into the following tool, where we'll estimate your household's percentile ranking among all U.S. households, based on data for 2016 that was recently published by the U.S. Census Bureau. Hopefully, you'll be entering a positive number, but if not, our tool can handle if your household is underwater and you have to enter a negative value. If you're reading this article on a site that republishes our RSS news feed, please click through to our site to access a working version of the tool.

Household Net Wealth Data
Input Data Values
Your Household Net Worth

Estimated Household Net Worth Percentile Ranking
Calculated Results Values
Your Household's Net Worth Percentile

Now you have a fairly good sense of what percentage of all 129,600,000 U.S. households have a net worth that is either less than or equal to yours! The chart below shows our model for the distribution of net worth in the United States and how it compares to the data recorded by the U.S. Census.

Estimated U.S. Distribution of Net Worth, 2016

Overall, the tool is generally accurate to within about 1.5 percentiles of the reported data, which is pretty good given how we modeled the data, where we spliced two very different regressions to generate our results.

In addition to the Census Bureau's wealth distribution data, the Federal Reserve's Survey of Consumer Finances provides an alternate source of data for household net worth in the U.S. The SCF is conducted every three years, where the data for 2019 will likely become available in late October 2020.

If you want to find out how your household ranks to the nearest half percentile according to the Federal Reserve's survey data, be sure to check out Don't Quit Your Day Job's Net Worth Percentile Calculator. Better still, if you want to find out how your household's net worth ranks among people in your age group, DQYDJ's Net Worth by Age Calculator has you covered!

Finally, we discovered that Microsoft (NYSE: MSFT) chairman Bill Gates had the highest reported net worth in 2016 thanks to the value of the shares he owns in the company he founded, which at $75 billion, would place him just off the top right end of the chart. The second highest net worth for an American belongs to Warren Buffett, whose accumulated net wealth over the last 49 years as the head of Berkshire Hathaway (NYSE: BRK.A, BRK.B) would appear on the chart at $60.8 billion (equivalent to a natural logarithm of 24.8).

References

U.S. Census Bureau. Net Worth and Asset Ownership of Households: 2016. [Excel Spreadsheet]. 25 September 2019. Accessed 19 October 2019.

Forbes. The Full List Of Every American Billionaire 2016. [Online Article]. 1 March 2016.

Clementi, F.; Gallegati, M.; and Kaniadakis, G. A generalized statistical model for the distribution of wealth. Journal of Statistical Mechanics: Theory and Experiment, 2012, P12006. https://doi.org/10.1088/1742-5468/2012/12/P12006. [Ungated PDF Document]. 6 December 2012.

Hozo, Stela Pudar; Djulbegovic, Benjamin; and Hozo, Iztok. Estimating the mean and variance from the median, range, and the size of a sample. BMC Medical Research Methodology, volume 5, Article number: 13 (2005). https://doi.org/10.1186/1471-2288-5-13. 20 April 2005.

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October 21, 2019

For a market that got almost every bit of positive news it could have been hoping for in the week before last, the S&P 500 (Index: SPX) didn't carry any momentum into the third week of October 2019.

The proof can be found in the latest update to our spaghetti forecast chart for the index, where we find the S&P 500 skimmed along and just below the top edge of the redzone forecast range we added to the chart just last week.

Alternative Futures - S&P 500 - 2019Q4 - Standard Model with Redzone Forecast with 50/50 Split Between 2019Q4 and 2020Q1 from 8 Oct 2019 to 8 Nov 2019 - Snapshot on 18 Oct 2019

That range assumes that the S&P 500 will track along with investors roughly equally splitting their forward looking focus between the current quarter of 2019-Q4 and the upcoming future quarter of 2020-Q1 in setting today's stock prices. Should the trajectory of the S&P 500 break outside of the redzone range, that would be an indication that investors have focused much more strongly on one of these two quarters.

Much of that dynamic has hinged on investor expectations for what the Federal Reserve will do in upcoming months with interest rates and its new T-bill buying policy. Right now, investors are betting the Fed will announce it will cut the Federal Funds Rate by a quarter point at its meeting at the end of this month, which could be the last cut for a while if the rate change probabilities indicated by the CME Group's FedWatch Tool is any indication:

CME Group FedWatch Tool Probabilities of Federal Funds Rate Changing at Future FOMC Meeting Dates, Snapshot on 18 October 2019

And then, there's that little matter of corporate earnings, which will be rolling out over the next several weeks, as well as other economic news that might alter the focus of investors. Here are the more significant headlines we plucked out of the news stream during the week that was.

Monday, 14 October 2019
Tuesday, 15 October 2019
Wednesday, 16 October 2019
Thursday, 17 October 2019
Friday, 18 October 2019

Barry Ritholtz found five positives and five negatives and no political noise that might affect the market in the past week's economics and market-related news.

If only there were no political noise to have to filter out. Wouldn't that be something!

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October 18, 2019

Are prime numbers randomly distributed, or is there an underlying structure that can predict where they will occur?

If you can definitively answer that question, say by either proving or disproving the Riemann Hypothesis, which says that yes, there is such an underlying structure, there's a million dollar prize waiting for you.

But if you just want to explore some the patterns that can be found in how prime numbers are distributed, you might find the following 22-and-a-half minute video from 3Blue1Brown right up your alley!

As a bonus, in addition to an introduction to Dirichlet's prime number theorem, you'll also find out why the fraction 355/113 is a particularly good rational approximation for the value of pi!

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October 17, 2019

In 2017, the average rent in the U.S. was "too damn high". In 2018, according to the Consumer Expenditure Survey, it was even higher.

Average Annual Home Ownership and Rent Expenditures per U.S. Household Consumer Unit, 1984-2018

Remarkably, the rent rose even as the cost to own, as measured by the average annual combined cost of mortgage principal and interest payments, fell. From 2017 to 2018, the average household consumer unit expenditure for rent increased from $4,167 to $4,269, while the cost to own declined from $5,104 to $5,002.

Before going any further, we should recognize the data reported by the Consumer Expenditure Survey is spreading all these payments out over all household consumer units in the United States. In 2018, there were an estimated 131,439,000 household consumer units, where 48,632,430 (37%) paying rent, an equal number of homeowners making mortgage payments, and 34,174,140 homeowners (26%) with no mortgage payments.

Doing the math for renters, multiplying the average $4,167 in annual rent payments by 131,439,000 household consumer units, we estimate the total rent paid in 2018 adds up to $547.7 billion. Dividing that result by the estimated 48,632,430 rent payers, we find the average annual rent is $11,262. Dividing by 12 gives an average monthly rent of $938.51, which is indeed slightly higher than the $935 per month figure we previously calculated for 2017.

Doing the almost identical math for homeowners making mortgage payments, we estimate aggregate mortgage payments to be $657.5 billion, with the average annual total of mortgage payments working out to be $13,519, which corresponds to an average monthly principal and interest mortgage payment of $1,126.58.

The average monthly rent paid in the United States in 2018 is 83% of the cost of a simple mortgage payment that omits any homeowners' insurance payments or property taxes that might be included with it.

In case you're wondering what ever happened to Jimmy McMillan, the founder of the Rent Is Too Damn High political party in New York who ran for state governor in 2006 and 2010, he has retired from politics, but since the rent keeps rising, we can only wonder if he is considering making a comeback!

Data Sources

U.S. Bureau of Labor Statistics and U.S. Census Bureau.  Consumer Expenditure Survey.  Multiyear Tables.  [PDF Documents: 1984-1991, 1992-1999, 2000-2005, 2006-2012, 2013-2018]. Reference Directory: https://www.bls.gov/cex/csxmulti.htm. 10 September 2019. 

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October 16, 2019

Americans collectively spent over $447.5 billion of their own money to cover the cost of unsubsidized health insurance in 2018, an increase of 0.8% from the more than $443.8 billion spent in 2017. At an average annual cost of $3,405 per household consumer unit however, 2018's spending represents the first year over year decline in this category of consumer expenditures since 1996, falling from 2017's average cost per household consumer unit of $3,414.

Average Annual Expenditures for Health Insurance per Household Consumer Unit, 1984-2018

This data comes from Consumer Expenditure Survey (CEX), which shows the continuing effect of the skyrocketing cost of health insurance caused by the passage and implementation of the Affordable Care Act during the Obama administration. In this case, the rapid escalation of health insurance costs to higher income earning households that could previously afford coverage may be prompting them to choose to become uninsured, which would contribute to the indicated reduction in average cost.

From 2017 to 2018, the number of individual uninsured Americans rose by 1.9 million, from 25.6 million to 27.5 million, which the U.S. Census Bureau reveals a very large portion of this increase was uniquely concentrated in households earning well above the median household income of $61,392 for 2018:

Between 2017 and 2018, overall health insurance coverage decreased 1.0 percentage point for people in families with income from 300 to 399 percent of poverty and 0.8 percentage points for people in families with income at or above 400 percent of poverty. During this time, the overall health insurance coverage rate did not statistically change for any other income-to-poverty group.

Here's how that translates into the number of affected individuals:

The number of uninsured Americans in households with income above 400 percent of the poverty line increased by 1.1 million from 2017 to 2018, and the number of uninsured in households with income above 300 percent of the poverty line — about $75,000 for a family of four — increased by 1.6 million.

Households in this category, which includes many headed by small business owners and self-employed income earners who don't have access to other employer-provided health insurance coverage, are largely choosing to go from paying top dollar or near-top dollar for health insurance to no such coverage, even though they would still be subject to additional income taxes from the Affordable Care Act's mandate penalty. For these higher income earning households, since the rising cost of coverage they must pay has been driven up by the requirements of the Affordable Care Act to the point where it far exceeds the value of tax subsidies available to them, dropping the amount they pay for family coverage from nearly $20,000 to $0 per household is having a noticeable effect on the overall average cost paid out of pocket by all American households for health insurance, which is being captured by the CEX data for 2018.

The Trump administration has introduced reforms aimed at arresting the skyrocketing cost of health insurance for these households in late 2018 to address their specific needs, which may not show an effect until the 2019 data becomes available.

Data Sources

U.S. Bureau of Labor Statistics and U.S. Census Bureau.  Consumer Expenditure Survey.  Multiyear Tables.  [PDF Documents: 1984-1991, 1992-1999, 2000-2005, 2006-2012, 2013-2018]. Reference Directory: https://www.bls.gov/cex/csxmulti.htm. 10 September 2019. 

U.S. Census Bureau. Health Insurance Coverage in the United States: 2018. [PDF Document]. 10 September 2019.

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Welcome to the blogosphere's toolchest! Here, unlike other blogs dedicated to analyzing current events, we create easy-to-use, simple tools to do the math related to them so you can get in on the action too! If you would like to learn more about these tools, or if you would like to contribute ideas to develop for this blog, please e-mail us at:

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