PK

Income Percentile Calculator for the United States in 2019

Economics October 14, 2019 by PK

Below is an individual income percentile calculator for the United States for 2019. Enter gross, pre-tax income earned by one person in full-year 2018 to compare to the US individual income distribution. (For a complete picture, see the household income calculator).

After try our income percentile by state and income percentile by city calculators.

(Math and methodology in our average, median, and top 1% individual income post)

Individual Income Percentiles for the US Income Distribution in 2019

In this graph we developed for the average individual income post, we compare single-person earnings between 2019 and 2018. 2018 numbers are CPI adjusted.

(Again, this means “full-year 2018” and “full-year 2017”, respectively. See the note in the average income post.)

Year over year individual income selected percentiles, USA

What was the median individual income in 2019?

In the United States, median individual income was $40,100.00 in 2019.

What was the average individual income in 2019?

In the United States, average individual income in the United States was $58,379.45 in 2019.

What was the top 1% individual income in 2019?

The United States threshold for a top 1% individual earner was $328,551.00 in 2019.

In 2019, what was the threshold for the top 10% individual income in the United States?

Top 10% of individual earnings started at $116,250.00 in the United states in 2019.

In 2019, what was the threshold for the top 5% individual income in the United States?

Top 5% of individual earnings started at $158,330.00 in the United states in 2019.

What other calculators do you have?

Thanks for asking! We have quite a few:

Net worth is in many ways a better measure of how well-off a household is. Income measures how much money comes in, but net worth measures wht you keep and grow. Try our net worth calculator and net worth by age calculator.

For a different slice of the same dataset, try our individual income by age calculator and household income calculator.

Individual Income Benchmarks in 2019

People love round numbers – I get it. Now let’s talk about how often people make the big benchmarks as an individual.

Take the exact numbers with a grain of salt (beware of false precision!). Just look at the absolute number as the rough number of workers who cleared the threshold.

How many people made $50,000 or more in 2019?

41.7% of workers, or around 72,624,482 people in the United States made $50,000 or more in 2019.

How many people made $100,000 or more in 2019?

“Six-figure income” is a common target income in the United States, and one which around 1/8th of workers hit. 13.8% of workers, or around 24,129,891 people in the United States made $100,000 or more in 2019.

How many people made $250,000 or more in 2019?

1.9% of workers, or around 3,365,738 people in the United States made $50,000 or more in 2019.

How many people made $500,000 or more in 2019?

.5% of workers, or around 801,705 people in the United States made $500,000 or more in 2019.

How many people made $1,000,000 or more in 2019?

Usually when we talk about millionaires we’re talking about net worth. However, ~.2% of workers – around 320,533 people in the United States – made $1,000,000 or more in 2019.

What is considered a good individual income?

A good income in the United States started around $46,000 in 2019. That’s the median individual income for a person who typically worked 40 or more hours per week. A better income is $75,875, which started the 75th percentile of earnings for 40+ hour workers.

These numbers are obviously very location dependent. What’s good at the country level does not necessarily translate to where you live. For example, in San Francisco County a family of 4 would be considered very low income at $75,875.

Live somewhere expensive? We’ve got you covered: see the income percentile by city and income percentile by state calculators for numbers in your area.

Source and Methodology on the 2019 Individual Income Percentile Calculator

Sarah Flood, Miriam King, Renae Rodgers, Steven Ruggles, and J. Robert Warren. Integrated Public Use Microdata Series, Current Population Survey: Version 6.0 [dataset]. Minneapolis, MN: IPUMS, 2019. https://doi.org/10.18128/D030.V6.0

For methodology, please see the individual income bracket post. The only additional screens in this calculator were for workers reporting 30+ and 40+ hours a week or work, respectively.

Want to see changes over time? Try our calculators from years past:

How did your individual income rank in 2019 vs. 2018?

Average, Median, Top 1%, and all United States Individual Income Percentiles in 2019

Personal Finance October 14, 2019 by PK

On this page I estimate United States Individual Income Brackets for 2019. I also calculate the average, median, and top 1% of individual incomes in the United States.

Individual incomes here are limited to Americans who worked (or wanted to work) in 2018. Incomes are earned between January and December 2018.

We also have research on household incomes.

Individual Income Benchmarks in 2019

The most important summary statistics for income are:

Median income
Average income
Top 1% income

What was the median individual income?

Median individual income was $40,100.00 in 2019 in the United States.

What was the average individual income?

Average individual income in 2019 in the United States was $58,379.45.

What is the top 1% individual income?

The threshold for a US worker to be in the top 1% in 2019 was $328,551.00.

Is median income the same as average income?

No, median and average income are not the same. They are different statistical measures:

Median individual income means half of all individual workers made more, while half made less money in full-year 2018.
Average individual income means we add up every worker’s earnings in full-year 2018 then divide by the number of workers.

We mentioned in the household income article research that median is the most important summary statistic. Especially with something like income, there are wide variations on earnings across workers.

Median is resistant to outliers in a way average isn’t – consider that it’s possible to make over a billion dollars in a year. If you only look at average the earnings will look higher than “most” people make because income is concentrated – you also see this (really, even worse) with net worth.

Selected United States Individual Income Percentiles for 2019 and 2019

As we showed in the household income research, some of the most interesting comparisons aren’t between percentiles – they’re between years.

Individual income is defined as all income earned assigned to one individual. Think:

Wage income
Business income
Investment income
Other income: see the list of all components

I adjusted 2018 individual income numbers to compare year over year as detailed by IPUMS CPS. To do it yourself, multiply 2018 dollar amounts by (.679/.663).

I caution you: this data isn’t longitudinal. People move between percentiles from year to year, people enter the workforce (new grads, long time unemployed)… and people leave (unemployment, retirement).

These numbers suggest avenues for further research, but don’t necessarily describe the experience of particular people over the last few years.

Comprehensive Individual Income Bracket Comparison 2018 vs. 2019

When I looked at the household income comparison, I told you 52% of household income breakpoints increased – a slight majority.

Surprisingly, a full 83.8% of individual income centiles (well, “”centile breakpoints””) increased in 2019 vs. 2018.

Absolute dollar change, CPI adjusted, between individual income bracket 2018-2019 — Change in household income percentile from 2018 to 2019 in US

It goes to show you never can tell how individual incomes interact with households. Just as individuals enter and exit the workforce, households form and dissolve.

2019 Individual Income Percentiles for the United States

To recap, the summary statistics for individual earners:

Top 1%: $328,551.00
Median individual income: $40,100.00
Average individual income: $58,379.45

Adjusted for inflation (CPI), top 1% and median were up 6.73% and .27%, respectively. Average individual income, CPI-adjusted, was up 2.01% in 2019.

Individual Income Percentile	2019	2018	Percentage Increase	Absolute Increase
1.00%	$0.00	$0.00	0.00%	$0.00
2.00%	$0.00	$0.00	0.00%	$0.00
3.00%	$301.00	$51.21	487.81%	$249.79
4.00%	$1,500.00	$921.72	62.74%	$578.28
5.00%	$2,500.00	$2,015.49	24.04%	$484.51
6.00%	$3,800.00	$2,808.17	35.32%	$991.83
7.00%	$5,000.00	$4,096.53	22.05%	$903.47
8.00%	$6,000.00	$5,120.66	17.17%	$879.34
9.00%	$7,303.00	$6,144.80	18.85%	$1,158.20
10.00%	$8,507.00	$7,168.93	18.66%	$1,338.07
11.00%	$10,000.00	$8,193.06	22.05%	$1,806.94
12.00%	$10,379.00	$9,729.26	6.68%	$649.74
13.00%	$12,000.00	$10,242.35	17.16%	$1,757.65
14.00%	$12,480.00	$11,267.51	10.76%	$1,212.49
15.00%	$14,000.00	$12,289.59	13.92%	$1,710.41
16.00%	$15,000.00	$13,313.73	12.67%	$1,686.27
17.00%	$15,050.00	$14,338.88	4.96%	$711.12
18.00%	$16,154.00	$15,361.99	5.16%	$792.01
19.00%	$17,509.00	$15,464.40	13.22%	$2,044.60
20.00%	$18,020.00	$16,410.70	9.81%	$1,609.30
21.00%	$19,104.00	$17,572.07	8.72%	$1,531.93
22.00%	$20,000.00	$18,435.41	8.49%	$1,564.59
23.00%	$20,001.00	$19,460.57	2.78%	$540.43
24.00%	$20,800.00	$20,482.65	1.55%	$317.35
25.00%	$22,000.00	$20,482.65	7.41%	$1,517.35
26.00%	$22,804.00	$21,077.68	8.19%	$1,726.32
27.00%	$23,825.00	$22,222.66	7.21%	$1,602.34
28.00%	$24,251.00	$22,752.13	6.59%	$1,498.87
29.00%	$25,000.00	$23,657.47	5.67%	$1,342.53
30.00%	$25,006.00	$24,580.21	1.73%	$425.79
31.00%	$26,000.00	$25,603.32	1.55%	$396.68
32.00%	$27,000.00	$25,604.34	5.45%	$1,395.66
33.00%	$28,000.00	$26,273.10	6.57%	$1,726.90
34.00%	$28,600.00	$27,122.11	5.45%	$1,477.89
35.00%	$30,000.00	$27,934.24	7.40%	$2,065.76
36.00%	$30,000.00	$28,682.89	4.59%	$1,317.11
37.00%	$30,002.00	$29,717.26	0.96%	$284.74
38.00%	$30,525.00	$30,723.98	-0.65%	-$198.98
39.00%	$31,800.00	$30,725.01	3.50%	$1,074.99
40.00%	$32,300.00	$30,865.31	4.65%	$1,434.69
41.00%	$33,502.00	$31,966.25	4.80%	$1,535.75
42.00%	$35,000.00	$32,779.42	6.77%	$2,220.58
43.00%	$35,000.00	$33,806.62	3.53%	$1,193.38
44.00%	$35,360.00	$35,127.75	0.66%	$232.25
45.00%	$36,107.00	$35,844.65	0.73%	$262.35
46.00%	$37,300.00	$35,875.37	3.97%	$1,424.63
47.00%	$38,175.00	$36,868.78	3.54%	$1,306.22
48.00%	$39,977.00	$37,894.96	5.49%	$2,082.04
49.00%	$40,000.00	$38,919.09	2.78%	$1,080.91
50.00%	$40,100.00	$39,990.33	0.27%	$109.67
51.00%	$41,120.00	$40,965.31	0.38%	$154.69
52.00%	$42,202.00	$40,975.55	2.99%	$1,226.45
53.00%	$43,690.00	$41,579.79	5.08%	$2,110.21
54.00%	$45,000.00	$43,013.57	4.62%	$1,986.43
55.00%	$45,211.00	$44,037.71	2.66%	$1,173.29
56.00%	$46,470.00	$45,573.91	1.97%	$896.09
57.00%	$48,000.00	$46,089.05	4.15%	$1,910.95
58.00%	$49,010.00	$46,898.11	4.50%	$2,111.89
59.00%	$50,000.00	$48,193.64	3.75%	$1,806.36
60.00%	$50,010.00	$49,501.46	1.03%	$508.54
61.00%	$50,545.00	$51,206.64	-1.29%	-$661.64
62.00%	$52,000.00	$51,214.83	1.53%	$785.17
63.00%	$53,026.00	$51,821.12	2.33%	$1,204.88
64.00%	$55,000.00	$53,255.93	3.27%	$1,744.07
65.00%	$55,510.00	$54,729.65	1.43%	$780.35
66.00%	$57,006.00	$56,328.32	1.20%	$677.68
67.00%	$58,908.00	$57,351.43	2.71%	$1,556.57
68.00%	$60,000.00	$59,399.70	1.01%	$600.30
69.00%	$60,106.00	$61,447.96	-2.18%	-$1,341.96
70.00%	$61,455.00	$61,468.45	-0.02%	-$13.45
71.00%	$63,300.00	$62,625.72	1.08%	$674.28
72.00%	$65,003.00	$64,654.52	0.54%	$348.48
73.00%	$66,760.00	$66,574.77	0.28%	$185.23
74.00%	$69,101.00	$68,134.53	1.42%	$966.47
75.00%	$70,125.00	$70,672.33	-0.77%	-$547.33
76.00%	$72,020.00	$71,730.26	0.40%	$289.74
77.00%	$74,953.00	$73,784.67	1.58%	$1,168.33
78.00%	$75,651.00	$76,809.95	-1.51%	-$1,158.95
79.00%	$78,146.00	$77,839.21	0.39%	$306.79
80.00%	$80,018.00	$80,957.69	-1.16%	-$939.69
81.00%	$82,076.00	$82,063.76	0.01%	$12.24
82.00%	$85,049.00	$85,003.02	0.05%	$45.98
83.00%	$88,113.00	$87,594.07	0.59%	$518.93
84.00%	$90,521.00	$91,711.09	-1.30%	-$1,190.09
85.00%	$94,750.00	$94,220.21	0.56%	$529.79
86.00%	$98,902.00	$98,547.17	0.36%	$354.83
87.00%	$100,478.00	$102,416.35	-1.89%	-$1,938.35
88.00%	$105,002.00	$104,497.38	0.48%	$504.62
89.00%	$110,010.00	$110,629.89	-0.56%	-$619.89
90.00%	$116,250.00	$116,820.77	-0.49%	-$570.77
91.00%	$121,500.00	$122,936.89	-1.17%	-$1,436.89
92.00%	$129,002.00	$129,144.16	-0.11%	-$142.16
93.00%	$137,542.00	$138,356.24	-0.59%	-$814.24
94.00%	$150,000.00	$148,952.94	0.70%	$1,047.06
95.00%	$158,330.00	$157,122.44	0.77%	$1,207.56
96.00%	$176,000.00	$174,348.36	0.95%	$1,651.64
97.00%	$200,300.00	$199,808.30	0.25%	$491.70
98.00%	$243,500.00	$231,234.83	5.30%	$12,265.17
99.00%	$328,551.00	$307,830.74	6.73%	$20,720.26

Methodology on 2019 United States Household Income Brackets

I source this data from the United States Census Bureau’s Annual ASEC survey, released in September 2019. I use harmonized data from the University of Minnesota’s Minnesota Population Center in R (thanks for making it easy for this engineer!).

Sarah Flood, Miriam King, Renae Rodgers, Steven Ruggles and J. Robert Warren. Integrated Public Use Microdata Series, Current Population Survey: Version 6.0 [dataset]. Minneapolis, MN: IPUMS, 2019. https://doi.org/10.18128/D030.V6.0

How can I cite your individual income data?

Feel free to quote an excerpt from the data and link here. Cite “Don’t Quit Your Day Job…” or “DQYDJ” (dealer’s choice!).

Also be certain to include the IPUMS citation in the previous section.

What is your ‘worker’ screen?

Because of many arguments over the years of doing this particular post, we’ve converged on an acceptable definition of workforce: people who are:

At least the age of 16
Labeled as ‘in workforce’
Report working 1 or more hours in a typical week
Report ‘want’ or ‘maybe want’ a job

How does this compare to the employment population ratio?

Because we are adding people who were in the workforce in a year plus people who ‘want’ and ‘maybe want’ a job our screen is more broad than the workforce measure. Specifically, it bumps our screen from ~64.5% of over 16s to ~67.5%.

Both measures are greater than a snapshot of employment to population in an individual month (see the current snapshot on FRED here). That’s merely a side effect of a 12 month period versus a snapshot.

Either way, this is a good screen. I cut it further for typical hours (but not a minimum weeks in year) worked in the individual income percentile calculator post.

Why don’t these numbers match the Social Security Administration’s earnings statistics?

The ASEC numbers are the gold standard estimates of income and poverty in the United States.

Seriously: the ASEC is the survey supplement where the Census Bureau creates the official poverty estimates for the United States. The numbers include all types of income including investment income. They don’t only include income where you would owe OASDI.

The highest earners every year have material income from multiple sources. Yet every year I hear arguments about the SSA data – let’s keep it to all income forms this year (🤞)?

How many samples are in the 2019 and 2018 data?

2019: 93,939 data-points representing an estimated 174,279,931 American workers.
2018: 93,820 data-points representing an estimated 173,874,158 American workers.

Is individual income gross or net?

All income numbers in this post are gross income, or before tax. The 2018 numbers are adjusted for CPI using the numbers in IPUMS’ instructions.

Can you compare this individual income data year over year?

This data is not longitudinal.

This means that it is a different set of people answering the survey than last year. The numbers I’m summarizing do not prove anything about how individuals – or households – have performed year over year.

See the above note – you can take strong hints from this data about where to research next. However, as a snapshot you can’t say anything about how individuals did year over year.

I’ll guess your next question: the University of Michigan’s PSID is a longitudinal income study.

Analysis of Individual Income Brackets in 2019

It’s one thing to talk theoretically about household construction versus individual earnings, but this year’s data really proves the value of our caution. 84% of individual income percentiles increased year over year, while “only” 52% of household income percentiles did the same.

See past editions of the average, median, and top 1% individual income post:

How did your income change from 2018 to 2019? How’s 2020 tracking? When’s the next recession?

2019 Household Income Percentile Calculator for the United States

Personal Finance October 8, 2019 by PK

On this page is a household income percentile calculator for the United States for 2019. Enter pre-tax (gross) household income earned between January and December 2018 to compare to household income percentiles in the full year.

You can find the methodology in the United States average income, median income, and income percentile post.

Afterwards, visit the income percentile by state and income percentile by city calculator. Or, try the individual income calculator.

Household Income Percentile Statistics in 2019

In our last post on household income brackets and summary statistics, I made a graph comparing some income percentiles year over year. Here’s what the household icome brackets look like for the 10th, 25th, 50th, 75th, 90th, 95th, and 99th (top 1%) percentiles:

2019 Household Income vs. 2018 in the United States, selected percentiles — Income Distribution in the US for Selected Percentiles (2019)

What was the United States average household income?

In 2019, average household income in the United States was $89,930.70.

What was the United States median household income?

In 2019, median household income in the United States was $63,030.00.

How many US households made $100,000 or more in 2019?

In 2019, about 39,162,447 households (30.4% of households) in the United States made $100,000 or more.

How many US households made $250,000 or More in 2019?

In 2019, about 6,365,893 households (4.9% of households) in the United States made $100,000 or more.

What was the top 10% household income percentile in 2019?

The threshold to be in the top 10% of household incomes in 2019 in the United States was $184,200.

What was the top 5% household income percentile in 2019?

The threshold to be in the top 5% of household incomes in 2019 in the United States was $248,304.00.

What is the top one percent household income in the US in 2019?

To be top 1% in the United States in 2019, you had to earn $475,116.00 or more as a household between January and December 2018.

Note: Net worth is a better proxy for the 1% (see our one percent in America article), yet most often one-percenter refers to income.

What other calculators do you have?

Thanks for being a reader! Want more calculators and interactive tools?

See our individual income by age calculator and individual income calculator. Also see our net worth calculator and net worth by age calculator.

Or, drink from the firehose on our calculator roundup page!

Source and Methodology on the 2018 Household Income Percentile Calculator

See the household income bracket article for details on methodology (but household income is very straightforward.

Care about annual changes? We’re done household income calculator posts since 2016. Here are the archived calculators:

Make sure you adjust for inflation.

How did your household income stack up to the household income distribution in 2019?

Average, Median, Top 1%, and all United States Household Income Percentiles in 2019

Economics October 7, 2019 by PK

On this page I estimate United States Household Income Brackets for 2019. I calculate the average, median, and top 1% household income in the United States. I also compute and show you every household income centile and a year-over-year comparison with 2018.

To repeat: this is household income data. 2019 income is income earned between January and December 2018.

We also have research on individual incomes.

Household Income Benchmarks in 2019

First up, I computed:

Median household income
Average household income
Top 1% household income

The median household income is the most important summary statistic. Medians are more resistant to outliers and better represent a “typical” household.

Median means the midpoint of household income: half of US households made more and half less.

What was the median household income?

Median household income was $63,030.00 in 2019.

What was the average household income?

Average household income in 2019 in the United States was $89,930.70.

What is the top 1% household income?

The threshold for a US household to be in the top 1% in 2019 was $475,116.00.

Selected United States Household Income Percentiles for 2019 and 2019

The most interesting comparison we do in our income series annually is our year over year comparison. Here we take the 10th, 25th, 50th/median, 75th, 90th, 95th, and 99th percentile of household incomes in the United States to see the changes in percentile thresholds.

The 2019 data is adjusted for CPI as detailed by IPUMS CPS. To do the math on your own, multiply 2018 dollar amounts by (.679/.663).

2019 Household Income vs. 2018 in the United States — Selected US Household Income Brackets, 2019 vs. 2018 (CPI adjusted)

Household income is defined as all income earned in the household:

Wage income
Business income
Investment income
Other income: see the list of all components

As I’ve said in past years: this incomes encompasses all the ways households make income, from stocks & bonds to wages. Like a tax return’s income entry, it’s not just wages from jobs.

In past years your objections about IRS and Social Security administration income data have been enthralling… but apples and oranges, friends. Read the above income component link and note how comprehensive this data is before rehashing objections which have been discussed here annually since 2011.

Comprehensive Household Income Bracket Comparison 2018 vs. 2019

In the 2018 data, nearly every household income percentile threshold saw an increase. That wasn’t the case in 2019, but we did see a slight majority of household income thresholds tick up:

Change in household income percentile from 2018 to 2019 in US

Very interestingly, the top 14% of thresholds (household income 86%+, or starting at $156,441.00) saw an increase. Before you speculate on what that means see the note on how data isn’t longitudinal.

But – it is interesting to observe. Let’s talk more in the conclusion.

Household Income Percentiles for the United States in 2019

To summarize, median household income in the United States was $63,030.00 and the threshold for a top 1% household was a whopping $475,116.00. Adjusted for inflation (CPI), the breakpoints were down 0.45% and up 6.78% vs. 2018, respectively.

Average household income in the United States was $89,930.70, up 1.40% adjusted for inflation.

Household Income Percentile	2019	2018	Percentage Increase	Absolute Increase
1%	$0.00	$0.00	0.00%	$0.00
2%	$600.00	$632.34	-5.11%	-$32.34
3%	$4,000.00	$4,147.74	-3.56%	-$147.74
4%	$7,000.00	$7,300.67	-4.12%	-$300.67
5%	$9,000.00	$9,032.85	-0.36%	-$32.85
6%	$10,000.00	$10,138.91	-1.37%	-$138.91
7%	$11,000.00	$11,060.63	-0.55%	-$60.63
8%	$12,104.00	$12,289.59	-1.51%	-$185.59
9%	$13,367.00	$13,383.08	-0.12%	-$16.08
10%	$14,603.00	$14,624.62	-0.15%	-$21.62
11%	$15,648.00	$15,413.07	1.52%	$234.93
12%	$16,859.00	$16,620.53	1.43%	$238.47
13%	$18,000.00	$17,662.19	1.91%	$337.81
14%	$19,021.00	$18,765.31	1.36%	$255.69
15%	$20,000.00	$20,092.46	-0.46%	-$92.46
16%	$21,032.00	$20,819.88	1.02%	$212.12
17%	$22,211.00	$22,059.82	0.69%	$151.18
18%	$23,623.00	$23,104.43	2.24%	$518.57
19%	$24,779.00	$24,462.15	1.30%	$316.85
20%	$25,555.00	$25,514.63	0.16%	$40.37
21%	$26,840.00	$26,126.32	2.73%	$713.68
22%	$28,000.00	$27,380.48	2.26%	$619.52
23%	$29,218.00	$28,675.72	1.89%	$542.28
24%	$30,004.00	$29,712.14	0.98%	$291.86
25%	$31,201.00	$30,725.01	1.55%	$475.99
26%	$32,300.00	$31,748.11	1.74%	$551.89
27%	$33,669.00	$32,796.99	2.66%	$872.01
28%	$35,000.00	$34,168.39	2.43%	$831.61
29%	$35,906.00	$35,651.08	0.72%	$254.92
30%	$37,000.00	$36,351.18	1.78%	$648.82
31%	$38,060.00	$37,688.08	0.99%	$371.92
32%	$39,712.00	$38,917.04	2.04%	$794.96
33%	$40,381.00	$40,148.99	0.58%	$232.01
34%	$41,957.00	$40,975.55	2.40%	$981.45
35%	$43,040.00	$42,235.23	1.91%	$804.77
36%	$44,599.00	$43,619.08	2.25%	$979.92
37%	$45,552.00	$45,082.32	1.04%	$469.68
38%	$47,000.00	$46,188.39	1.76%	$811.61
39%	$48,300.00	$47,647.90	1.37%	$652.10
40%	$50,000.00	$49,160.42	1.71%	$839.58
41%	$50,272.00	$50,594.21	-0.64%	-$322.21
42%	$51,801.00	$51,265.38	1.04%	$535.62
43%	$53,058.00	$52,746.69	0.59%	$311.31
44%	$54,890.00	$54,255.03	1.17%	$634.97
45%	$56,000.00	$55,849.64	0.27%	$150.36
46%	$57,435.00	$57,111.46	0.57%	$323.54
47%	$59,000.00	$58,858.96	0.24%	$141.04
48%	$60,015.00	$60,526.24	-0.84%	-$511.24
49%	$61,520.00	$61,505.23	0.02%	$14.77
50%	$63,030.00	$63,313.93	-0.45%	-$283.93
51%	$64,859.00	$65,153.36	-0.45%	-$294.36
52%	$66,110.00	$66,585.01	-0.71%	-$475.01
53%	$67,894.00	$68,223.09	-0.48%	-$329.09
54%	$69,563.00	$69,825.94	-0.38%	-$262.94
55%	$70,798.00	$71,691.34	-1.25%	-$893.34
56%	$72,521.00	$73,226.51	-0.96%	-$705.51
57%	$74,640.00	$75,064.87	-0.57%	-$424.87
58%	$75,830.00	$76,822.24	-1.29%	-$992.24
59%	$77,566.00	$78,442.63	-1.12%	-$876.63
60%	$79,526.00	$80,463.24	-1.16%	-$937.24
61%	$81,000.00	$81,981.58	-1.20%	-$981.58
62%	$83,020.00	$83,978.88	-1.14%	-$958.88
63%	$85,040.00	$85,967.91	-1.08%	-$927.91
64%	$87,004.00	$87,672.15	-0.76%	-$668.15
65%	$89,452.00	$90,063.26	-0.68%	-$611.26
66%	$91,001.00	$92,171.95	-1.27%	-$1,170.95
67%	$93,268.00	$93,954.67	-0.73%	-$686.67
68%	$95,572.00	$96,293.51	-0.75%	-$721.51
69%	$98,150.00	$98,609.15	-0.47%	-$459.15
70%	$100,201.00	$101,208.07	-1.00%	-$1,007.07
71%	$102,671.00	$102,745.79	-0.07%	-$74.79
72%	$105,100.00	$105,377.89	-0.26%	-$277.89
73%	$107,592.00	$108,051.66	-0.43%	-$459.66
74%	$110,200.00	$111,220.81	-0.92%	-$1,020.81
75%	$113,010.00	$113,842.59	-0.73%	-$832.59
76%	$116,115.00	$117,135.34	-0.87%	-$1,020.34
77%	$119,686.00	$120,151.25	-0.39%	-$465.25
78%	$122,300.00	$123,108.13	-0.66%	-$808.13
79%	$126,000.00	$127,022.49	-0.80%	-$1,022.49
80%	$130,000.00	$130,212.74	-0.16%	-$212.74
81%	$133,602.00	$133,691.72	-0.07%	-$89.72
82%	$138,000.00	$138,204.01	-0.15%	-$204.01
83%	$142,141.00	$142,496.72	-0.25%	-$355.72
84%	$147,100.00	$146,879.52	0.15%	$220.48
85%	$151,124.00	$151,993.59	-0.57%	-$869.59
86%	$156,441.00	$156,017.40	0.27%	$423.60
87%	$162,503.00	$161,681.35	0.51%	$821.65
88%	$169,000.00	$168,306.38	0.41%	$693.62
89%	$175,847.00	$175,210.23	0.36%	$636.77
90%	$184,200.00	$183,107.76	0.60%	$1,092.24
91%	$194,041.00	$191,460.71	1.35%	$2,580.29
92%	$203,606.00	$201,022.26	1.29%	$2,583.74
93%	$216,170.00	$211,185.84	2.36%	$4,984.16
94%	$231,175.00	$224,513.74	2.97%	$6,661.26
95%	$248,304.00	$242,064.42	2.58%	$6,239.58
96%	$272,000.00	$263,534.71	3.21%	$8,465.29
97%	$305,501.00	$296,284.84	3.11%	$9,216.16
98%	$359,173.00	$341,405.05	5.20%	$17,767.95
99%	$475,116.00	$444,939.38	6.78%	$30,176.62

51 of the 99 quoted percentiles saw an increase. That means roughly 52% of household income bracket thresholds increased between 2018 and 2019.

What is considered middle class income?

In 2019, middle class encompasses household income from $31,515 to $126,060. This definition of middle class is half of median household income to 2x median household income.

Of course, this is location dependent. We have higher resolution data you should look at for expensive locales:

Methodology on 2019 United States Household Income Brackets

Data originated in the United States Census Bureau’s Annual ASEC survey, first released in September 2019. The University of Minnesota’s Minnesota Population Center harmonizes it and makes it easy for us to create extracts to bring into R. Their take on the data was released first in October, 2019.

How can I cite your household income data?

You can quote an excerpt and link back to this page, citing “Don’t Quit Your Day Job…”. Also include the IPUMS citation right before this section.

How many samples are in the 2019 and 2018 data?

2019: 68,345 data-points representing an estimated 128,674,487 American households.
2018: 67,909 data-points representing an estimated 127,679,100 American households.

Is household income gross or net?

The household income data in this post is gross income, that is before tax income. I make no adjustments to the 2019 data for anything like taxes or cost of living.

The 2018 data is adjusted for inflation to fairly compare it to the cost of living one year later.

Can you compare this household income data year over year?

Yes, you can compare household income data but you need to be very careful with your comparisons.

This data is not longitudinal.

You can not draw any conclusions about the performance of individual households from this data. Households in certain income brackets move up or down the income spectrum, but the data as presented doesn’t give any history or hint of movement.

The only fair way to draw conclusions about the performance of last year’s households is with repeat surveys given to the same subjects.

Analysis of Household Income in 2019

To start, if you’d rather see the data in interactive form we built a household income percentile calculator. In this initial analysis of the 2019 United States household income data, a few things stuck out.

Household Income Round Number Thresholds

First, we are rapidly approaching two round number thresholds in 2019:

Average household income is nearing $90,000
Top 1% household income is nearing $500,000

$500,000 is an interesting breakpoint. It’s not interesting because “the math doesn’t scratch”, but rather that “half a million dollars” feels like an important threshold.

Ignoring inflation, the top 1% threshold increased 9.4% year over year. If we print a similar increase next year you could be looking at an income of $520,000 to crack the top 1% of households in 2020.

Household Income Bracket Thresholds Increasing

Also interesting were the household income brackets that increased dollar thresholds:

The 86th percentile to the 99th percentile increased
The 16th percentile to the 40th percentile increased

Now, you can’t draw conclusions because the data isn’t longitudinal. (Think: households can be forming or merging, people can be immigrating and emigrating, families can time buying and selling decisions, etc.).

But – it was interesting to see the middle percentiles struggling while the lower-middles and upper percentile thresholds soar. Longitudinal data aside, it suggests some interesting paths for research.

See the post from 2017 and the counterpart from 2018.

How did your 2019 income compare to your 2018 household income? What do you expect in 2020? When do you expect the United States will see its next recession?

Historical Home Prices: Monthly Median Value in the US from 1953-2019

Economics Real Estate October 3, 2019 by PK

Below, I provide and graph historical monthly median single-family home values in the United States. Importantly, this data is non-seasonally adjusted and based on sales of existing homes.

The data includes home prices from January 1953 until July 2019. There is a historical home price series using nominal prices and one adjusted for inflation.

Historical Median Home Value

I needed historical median home prices on the United States housing market – and (of course) this data doesn’t really exist.

The Census Bureau provides data on median new home sales, but nothing for existing home sales. This data uses the non-seasonally adjusted housing price index data from Robert Shiller and the FHFA to mash up these values.

Historical median home value in the US, nominal and real — Graph of the median home price in the US since 1953: inflation adjusted and nominal

United States Median Home Price History

Month of Observation	Median Home Price (NSA)	Inflation Adjusted Home Price
1953-01-01	$ 18,080.26	$ 174,393.58
1953-02-01	$ 18,080.26	$ 175,051.66
1953-03-01	$ 18,080.26	$ 174,393.58
1953-04-01	$ 18,122.25	$ 174,798.67
1953-05-01	$ 18,143.25	$ 174,345.78
1953-06-01	$ 18,143.25	$ 173,695.24
1953-07-01	$ 18,185.25	$ 174,097.31
1953-08-01	$ 18,206.25	$ 173,650.40
1953-09-01	$ 18,227.25	$ 173,850.69
1953-10-01	$ 18,227.25	$ 173,206.80
1953-11-01	$ 18,206.25	$ 173,650.40
1953-12-01	$ 18,206.25	$ 173,650.40
1954-01-01	$ 18,206.25	$ 173,650.40
1954-02-01	$ 18,227.25	$ 173,850.69
1954-03-01	$ 18,227.25	$ 173,850.69
1954-04-01	$ 18,206.25	$ 174,298.35
1954-05-01	$ 18,206.25	$ 173,650.40
1954-06-01	$ 18,227.25	$ 173,850.69
1954-07-01	$ 18,290.25	$ 174,451.55
1954-08-01	$ 18,332.24	$ 174,852.13
1954-09-01	$ 18,374.24	$ 175,906.64
1954-10-01	$ 18,353.24	$ 175,705.60
1954-11-01	$ 18,353.24	$ 175,705.60
1954-12-01	$ 18,374.24	$ 176,565.46
1955-01-01	$ 18,395.24	$ 176,767.25
1955-02-01	$ 18,332.24	$ 176,161.89
1955-03-01	$ 18,290.25	$ 175,758.31
1955-04-01	$ 18,185.25	$ 174,749.36
1955-05-01	$ 18,185.25	$ 174,749.36
1955-06-01	$ 18,269.25	$ 175,556.52
1955-07-01	$ 18,332.24	$ 175,504.56
1955-08-01	$ 18,437.24	$ 176,509.75
1955-09-01	$ 18,479.24	$ 176,254.15
1955-10-01	$ 18,458.24	$ 176,053.86
1955-11-01	$ 18,416.24	$ 175,653.29
1955-12-01	$ 18,374.24	$ 175,906.64
1956-01-01	$ 18,332.24	$ 175,504.56
1956-02-01	$ 18,269.25	$ 174,901.46
1956-03-01	$ 18,206.25	$ 174,298.35
1956-04-01	$ 18,122.25	$ 172,849.24
1956-05-01	$ 18,143.25	$ 172,408.61
1956-06-01	$ 18,332.24	$ 172,923.62
1956-07-01	$ 18,479.24	$ 173,037.84
1956-08-01	$ 18,605.23	$ 174,855.80
1956-09-01	$ 18,584.23	$ 174,021.01
1956-10-01	$ 18,563.24	$ 173,192.28
1956-11-01	$ 18,521.24	$ 172,800.45
1956-12-01	$ 18,542.24	$ 172,369.57
1957-01-01	$ 18,605.23	$ 172,955.19
1957-02-01	$ 18,773.23	$ 173,886.84
1957-03-01	$ 18,773.23	$ 173,261.35
1957-04-01	$ 18,899.22	$ 173,799.00
1957-05-01	$ 18,962.22	$ 173,755.55
1957-06-01	$ 18,899.22	$ 172,562.00
1957-07-01	$ 18,899.22	$ 171,342.48
1957-08-01	$ 18,899.22	$ 171,342.48
1957-09-01	$ 18,962.22	$ 171,913.62
1957-10-01	$ 19,067.21	$ 172,865.52
1957-11-01	$ 19,067.21	$ 172,256.84
1957-12-01	$ 19,046.22	$ 172,067.13
1958-01-01	$ 19,067.21	$ 171,052.25
1958-02-01	$ 19,067.21	$ 171,052.25
1958-03-01	$ 19,235.21	$ 171,360.99
1958-04-01	$ 19,277.21	$ 171,140.90
1958-05-01	$ 19,319.20	$ 171,513.75
1958-06-01	$ 19,214.21	$ 170,581.61
1958-07-01	$ 19,214.21	$ 169,993.40
1958-08-01	$ 19,193.21	$ 170,395.19
1958-09-01	$ 19,130.21	$ 169,835.90
1958-10-01	$ 19,109.21	$ 169,649.47
1958-11-01	$ 19,151.21	$ 169,436.05
1958-12-01	$ 19,172.21	$ 170,208.76
1959-01-01	$ 19,130.21	$ 169,250.26
1959-02-01	$ 19,109.21	$ 169,649.47
1959-03-01	$ 19,109.21	$ 169,649.47
1959-04-01	$ 19,109.21	$ 169,064.48
1959-05-01	$ 19,193.21	$ 169,807.62
1959-06-01	$ 19,193.21	$ 169,224.08
1959-07-01	$ 19,130.21	$ 168,091.01
1959-08-01	$ 19,109.21	$ 167,906.50
1959-09-01	$ 19,151.21	$ 167,701.21
1959-10-01	$ 19,256.21	$ 168,047.08
1959-11-01	$ 19,277.21	$ 168,230.34
1959-12-01	$ 19,193.21	$ 167,497.31
1960-01-01	$ 19,256.21	$ 168,620.62
1960-02-01	$ 19,256.21	$ 168,047.08
1960-03-01	$ 19,256.21	$ 168,047.08
1960-04-01	$ 19,256.21	$ 167,477.43
1960-05-01	$ 19,214.21	$ 167,112.16
1960-06-01	$ 19,172.21	$ 166,183.55
1960-07-01	$ 19,172.21	$ 166,183.55
1960-08-01	$ 19,256.21	$ 166,911.63
1960-09-01	$ 19,340.20	$ 167,639.70
1960-10-01	$ 19,403.20	$ 167,057.00
1960-11-01	$ 19,340.20	$ 166,514.61
1960-12-01	$ 19,340.20	$ 166,514.61
1961-01-01	$ 19,340.20	$ 166,514.61
1961-02-01	$ 19,298.20	$ 166,153.01
1961-03-01	$ 19,340.20	$ 166,514.61
1961-04-01	$ 19,256.21	$ 165,791.42
1961-05-01	$ 19,319.20	$ 166,333.81
1961-06-01	$ 19,298.20	$ 166,153.01
1961-07-01	$ 19,361.20	$ 165,584.10
1961-08-01	$ 19,382.20	$ 166,318.09
1961-09-01	$ 19,382.20	$ 165,763.69
1961-10-01	$ 19,382.20	$ 165,763.69
1961-11-01	$ 19,487.20	$ 166,661.65
1961-12-01	$ 19,529.20	$ 167,020.84
1962-01-01	$ 19,550.19	$ 167,200.43
1962-02-01	$ 19,508.20	$ 166,286.96
1962-03-01	$ 19,508.20	$ 166,286.96
1962-04-01	$ 19,508.20	$ 165,736.34
1962-05-01	$ 19,613.19	$ 166,628.35
1962-06-01	$ 19,634.19	$ 166,806.76
1962-07-01	$ 19,634.19	$ 166,256.24
1962-08-01	$ 19,634.19	$ 166,256.24
1962-09-01	$ 19,613.19	$ 165,532.11
1962-10-01	$ 19,571.19	$ 165,177.65
1962-11-01	$ 19,592.19	$ 165,354.88
1962-12-01	$ 19,592.19	$ 165,354.88
1963-01-01	$ 19,613.19	$ 165,532.11
1963-02-01	$ 19,613.19	$ 165,532.11
1963-03-01	$ 19,718.19	$ 165,872.63
1963-04-01	$ 19,802.18	$ 166,579.22
1963-05-01	$ 19,760.19	$ 166,225.92
1963-06-01	$ 19,760.19	$ 165,682.70
1963-07-01	$ 19,802.18	$ 165,494.01
1963-08-01	$ 19,802.18	$ 165,494.01
1963-09-01	$ 19,802.18	$ 165,494.01
1963-10-01	$ 19,802.18	$ 164,956.69
1963-11-01	$ 19,928.18	$ 166,006.26
1963-12-01	$ 20,012.18	$ 166,166.47
1964-01-01	$ 20,012.18	$ 166,166.47
1964-02-01	$ 20,075.17	$ 166,689.55
1964-03-01	$ 20,075.17	$ 166,689.55
1964-04-01	$ 20,012.18	$ 166,166.47
1964-05-01	$ 19,928.18	$ 165,469.02
1964-06-01	$ 19,991.18	$ 165,456.65
1964-07-01	$ 20,033.17	$ 165,271.11
1964-08-01	$ 20,096.17	$ 166,325.64
1964-09-01	$ 20,159.17	$ 166,310.55
1964-10-01	$ 20,201.17	$ 166,657.03
1964-11-01	$ 20,264.17	$ 166,640.93
1964-12-01	$ 20,264.17	$ 166,640.93
1965-01-01	$ 20,390.16	$ 167,677.04
1965-02-01	$ 20,390.16	$ 167,677.04
1965-03-01	$ 20,327.16	$ 166,624.93
1965-04-01	$ 20,285.16	$ 165,751.11
1965-05-01	$ 20,264.17	$ 165,579.52
1965-06-01	$ 20,264.17	$ 164,531.55
1965-07-01	$ 20,306.16	$ 164,872.55
1965-08-01	$ 20,306.16	$ 164,872.55
1965-09-01	$ 20,306.16	$ 164,872.55
1965-10-01	$ 20,432.16	$ 165,372.22
1965-11-01	$ 20,537.15	$ 166,222.02
1965-12-01	$ 20,600.15	$ 166,207.59
1966-01-01	$ 20,663.15	$ 166,715.87
1966-02-01	$ 20,621.15	$ 165,337.16
1966-03-01	$ 20,621.15	$ 164,822.09
1966-04-01	$ 20,642.15	$ 163,968.33
1966-05-01	$ 20,684.15	$ 164,301.93
1966-06-01	$ 20,726.15	$ 164,127.41
1966-07-01	$ 20,747.15	$ 163,788.18
1966-08-01	$ 20,684.15	$ 162,292.12
1966-09-01	$ 20,684.15	$ 162,292.12
1966-10-01	$ 20,768.14	$ 161,960.59
1966-11-01	$ 20,768.14	$ 161,960.59
1966-12-01	$ 20,852.14	$ 162,615.64
1967-01-01	$ 20,852.14	$ 162,615.64
1967-02-01	$ 20,852.14	$ 162,615.64
1967-03-01	$ 20,705.15	$ 160,980.01
1967-04-01	$ 20,789.14	$ 161,144.75
1967-05-01	$ 20,915.14	$ 161,633.07
1967-06-01	$ 20,957.14	$ 161,471.28
1967-07-01	$ 20,957.14	$ 160,987.83
1967-08-01	$ 21,083.13	$ 161,472.24
1967-09-01	$ 21,083.13	$ 160,991.67
1967-10-01	$ 21,167.13	$ 161,153.45
1967-11-01	$ 21,230.13	$ 161,154.87
1967-12-01	$ 21,335.12	$ 161,474.14
1968-01-01	$ 21,314.12	$ 160,369.08
1968-02-01	$ 21,419.12	$ 160,687.85
1968-03-01	$ 21,377.12	$ 159,905.21
1968-04-01	$ 21,377.12	$ 159,440.37
1968-05-01	$ 21,314.12	$ 158,509.73
1968-06-01	$ 21,482.11	$ 158,838.26
1968-07-01	$ 21,566.11	$ 158,545.52
1968-08-01	$ 21,629.11	$ 158,554.34
1968-09-01	$ 21,629.11	$ 158,102.62
1968-10-01	$ 21,776.10	$ 158,275.25
1968-11-01	$ 22,028.09	$ 159,654.51
1968-12-01	$ 22,217.08	$ 160,570.69
1969-01-01	$ 22,322.08	$ 160,876.36
1969-02-01	$ 22,427.08	$ 160,730.09
1969-03-01	$ 22,616.07	$ 160,737.60
1969-04-01	$ 22,637.07	$ 160,000.41
1969-05-01	$ 22,742.06	$ 160,300.93
1969-06-01	$ 22,805.06	$ 159,866.59
1969-07-01	$ 23,015.05	$ 160,461.82
1969-08-01	$ 23,162.05	$ 160,613.76
1969-09-01	$ 23,330.04	$ 161,342.62
1969-10-01	$ 23,519.03	$ 161,777.51
1969-11-01	$ 23,624.03	$ 161,633.07
1969-12-01	$ 23,771.02	$ 161,775.98
1970-01-01	$ 24,002.01	$ 162,915.87
1970-02-01	$ 24,170.00	$ 163,192.69
1970-03-01	$ 24,296.00	$ 163,184.52
1970-04-01	$ 24,400.99	$ 162,612.66
1970-05-01	$ 24,589.99	$ 163,447.60
1970-06-01	$ 24,757.98	$ 163,715.97
1970-07-01	$ 24,820.98	$ 163,290.85
1970-08-01	$ 25,051.97	$ 164,810.47
1970-09-01	$ 25,303.96	$ 165,618.92
1970-10-01	$ 25,429.95	$ 165,598.69
1970-11-01	$ 25,576.95	$ 165,714.71
1970-12-01	$ 25,723.94	$ 165,829.57
1971-01-01	$ 25,786.94	$ 166,235.69
1971-02-01	$ 25,723.94	$ 165,413.96
1971-03-01	$ 25,723.94	$ 165,000.43
1971-04-01	$ 25,807.94	$ 165,126.39
1971-05-01	$ 25,996.93	$ 165,510.12
1971-06-01	$ 26,269.92	$ 166,012.29
1971-07-01	$ 26,311.92	$ 165,869.15
1971-08-01	$ 26,395.91	$ 165,990.82
1971-09-01	$ 26,458.91	$ 166,386.98
1971-10-01	$ 26,542.91	$ 166,507.09
1971-11-01	$ 26,752.90	$ 167,824.39
1971-12-01	$ 26,815.90	$ 167,401.00
1972-01-01	$ 26,899.89	$ 167,925.35
1972-02-01	$ 26,962.89	$ 167,503.52
1972-03-01	$ 26,941.89	$ 166,968.78
1972-04-01	$ 26,983.89	$ 166,826.10
1972-05-01	$ 27,067.88	$ 166,943.13
1972-06-01	$ 27,235.88	$ 167,576.41
1972-07-01	$ 27,508.87	$ 168,448.15
1972-08-01	$ 27,613.86	$ 168,688.48
1972-09-01	$ 27,592.86	$ 168,159.82
1972-10-01	$ 27,571.86	$ 167,237.37
1972-11-01	$ 27,592.86	$ 166,970.01
1972-12-01	$ 27,613.86	$ 166,703.91
1973-01-01	$ 27,550.86	$ 165,933.17
1973-02-01	$ 27,550.86	$ 164,772.80
1973-03-01	$ 27,571.86	$ 163,375.07
1973-04-01	$ 27,571.86	$ 162,250.93
1973-05-01	$ 27,634.86	$ 161,510.34
1973-06-01	$ 27,697.86	$ 160,779.80
1973-07-01	$ 27,676.86	$ 160,295.25
1973-08-01	$ 27,928.85	$ 158,885.43
1973-09-01	$ 28,033.84	$ 159,129.90
1973-10-01	$ 28,243.84	$ 158,915.55
1973-11-01	$ 28,369.83	$ 158,581.17
1973-12-01	$ 28,558.82	$ 158,600.99
1974-01-01	$ 28,789.81	$ 158,511.40
1974-02-01	$ 29,020.80	$ 157,752.05
1974-03-01	$ 29,335.79	$ 157,462.62
1974-04-01	$ 29,440.79	$ 157,367.75
1974-05-01	$ 29,587.78	$ 156,200.96
1974-06-01	$ 29,755.77	$ 155,805.48
1974-07-01	$ 29,902.77	$ 155,307.35
1974-08-01	$ 30,175.76	$ 154,844.48
1974-09-01	$ 30,469.74	$ 154,499.07
1974-10-01	$ 30,721.73	$ 154,252.56
1974-11-01	$ 30,952.72	$ 154,205.27
1974-12-01	$ 31,435.70	$ 155,404.44
1975-01-01	$ 32,033.50	$ 157,751.79
1975-02-01	$ 32,086.75	$ 156,810.11
1975-03-01	$ 32,169.16	$ 156,616.22
1975-04-01	$ 32,222.41	$ 156,282.37
1975-05-01	$ 32,318.77	$ 155,865.78
1975-06-01	$ 32,298.49	$ 154,605.50
1975-07-01	$ 32,472.18	$ 153,716.24
1975-08-01	$ 32,664.89	$ 154,343.73
1975-09-01	$ 32,994.54	$ 155,044.71
1975-10-01	$ 33,239.23	$ 155,341.03
1975-11-01	$ 33,475.05	$ 155,311.52
1975-12-01	$ 33,570.14	$ 155,191.43
1976-01-01	$ 33,693.12	$ 155,479.81
1976-02-01	$ 33,757.78	$ 155,219.85
1976-03-01	$ 34,054.46	$ 156,303.87
1976-04-01	$ 34,395.51	$ 157,306.42
1976-05-01	$ 34,801.22	$ 158,035.12
1976-06-01	$ 34,908.99	$ 157,687.22
1976-07-01	$ 35,196.79	$ 158,151.94
1976-08-01	$ 35,426.27	$ 158,351.12
1976-09-01	$ 35,681.11	$ 158,936.43
1976-10-01	$ 35,797.75	$ 158,629.79
1976-11-01	$ 36,005.68	$ 159,276.09
1976-12-01	$ 36,304.89	$ 160,047.81
1977-01-01	$ 36,606.64	$ 160,550.47
1977-02-01	$ 37,036.44	$ 160,786.41
1977-03-01	$ 37,566.40	$ 161,990.75
1977-04-01	$ 38,234.56	$ 163,497.99
1977-05-01	$ 38,707.47	$ 164,696.75
1977-06-01	$ 39,000.34	$ 164,849.37
1977-07-01	$ 39,402.25	$ 165,729.10
1977-08-01	$ 39,801.62	$ 166,861.80
1977-09-01	$ 40,322.71	$ 168,495.73
1977-10-01	$ 40,829.85	$ 170,060.97
1977-11-01	$ 41,252.04	$ 170,986.72
1977-12-01	$ 41,624.79	$ 171,976.08
1978-01-01	$ 42,044.45	$ 172,598.19
1978-02-01	$ 42,516.09	$ 173,424.42
1978-03-01	$ 43,108.18	$ 174,452.81
1978-04-01	$ 43,673.64	$ 175,358.20
1978-05-01	$ 44,273.33	$ 176,112.45
1978-06-01	$ 44,940.22	$ 176,845.97
1978-07-01	$ 45,572.88	$ 177,970.76
1978-08-01	$ 46,173.84	$ 179,498.00
1978-09-01	$ 46,658.16	$ 180,017.00
1978-10-01	$ 47,110.78	$ 180,138.00
1978-11-01	$ 47,605.24	$ 181,218.46
1978-12-01	$ 48,169.44	$ 182,553.62
1979-01-01	$ 48,813.50	$ 183,369.39
1979-02-01	$ 49,427.14	$ 183,524.91
1979-03-01	$ 50,082.62	$ 184,093.81
1979-04-01	$ 50,733.03	$ 184,371.44
1979-05-01	$ 51,391.04	$ 184,411.91
1979-06-01	$ 52,041.45	$ 184,679.49
1979-07-01	$ 52,624.66	$ 184,705.36
1979-08-01	$ 53,154.62	$ 184,795.86
1979-09-01	$ 53,604.71	$ 184,362.12
1979-10-01	$ 54,080.15	$ 184,513.28
1979-11-01	$ 54,468.12	$ 184,123.04
1979-12-01	$ 54,796.49	$ 183,301.04
1980-01-01	$ 55,074.15	$ 181,625.05
1980-02-01	$ 55,392.38	$ 180,127.73
1980-03-01	$ 55,865.29	$ 178,943.97
1980-04-01	$ 56,388.91	$ 178,614.30
1980-05-01	$ 56,788.28	$ 178,120.12
1980-06-01	$ 57,133.14	$ 177,251.58
1980-07-01	$ 57,529.97	$ 178,482.74
1980-08-01	$ 57,865.95	$ 178,232.00
1980-09-01	$ 58,147.42	$ 177,606.44
1980-10-01	$ 58,387.04	$ 176,655.91
1980-11-01	$ 58,621.59	$ 175,913.46
1980-12-01	$ 58,853.61	$ 174,972.53
1981-01-01	$ 59,034.91	$ 174,099.38
1981-02-01	$ 59,272.00	$ 173,008.83
1981-03-01	$ 59,625.73	$ 172,861.39
1981-04-01	$ 60,156.96	$ 173,227.06
1981-05-01	$ 60,575.35	$ 173,072.14
1981-06-01	$ 60,967.12	$ 172,653.35
1981-07-01	$ 61,280.27	$ 171,645.65
1981-08-01	$ 61,594.70	$ 171,217.92
1981-09-01	$ 61,711.34	$ 169,885.64
1981-10-01	$ 61,795.02	$ 169,751.72
1981-11-01	$ 61,798.83	$ 169,218.64
1981-12-01	$ 61,848.27	$ 168,813.54
1982-01-01	$ 61,890.11	$ 168,390.32
1982-02-01	$ 61,990.27	$ 168,127.97
1982-03-01	$ 61,956.04	$ 168,212.94
1982-04-01	$ 62,037.18	$ 167,723.31
1982-05-01	$ 62,118.32	$ 166,364.93
1982-06-01	$ 62,113.25	$ 164,293.39
1982-07-01	$ 62,096.77	$ 163,407.49
1982-08-01	$ 62,068.88	$ 162,999.73
1982-09-01	$ 62,090.43	$ 162,723.23
1982-10-01	$ 62,091.70	$ 162,229.42
1982-11-01	$ 62,095.50	$ 162,570.46
1982-12-01	$ 62,200.73	$ 163,513.37
1983-01-01	$ 62,408.66	$ 163,724.47
1983-02-01	$ 62,733.23	$ 164,407.84
1983-03-01	$ 62,993.14	$ 165,089.00
1983-04-01	$ 63,317.71	$ 164,761.54
1983-05-01	$ 63,635.94	$ 164,588.07
1983-06-01	$ 63,947.83	$ 164,896.07
1983-07-01	$ 64,312.97	$ 165,173.61
1983-08-01	$ 64,598.24	$ 165,409.53
1983-09-01	$ 64,770.67	$ 165,027.55
1983-10-01	$ 64,892.38	$ 164,846.56
1983-11-01	$ 64,981.13	$ 164,745.79
1983-12-01	$ 65,151.02	$ 165,013.45
1984-01-01	$ 65,341.20	$ 164,520.68
1984-02-01	$ 65,551.66	$ 164,244.68
1984-03-01	$ 65,850.88	$ 164,672.76
1984-04-01	$ 66,219.82	$ 164,792.29
1984-05-01	$ 66,636.94	$ 165,349.20
1984-06-01	$ 67,021.10	$ 165,821.32
1984-07-01	$ 67,391.31	$ 166,096.61
1984-08-01	$ 67,714.61	$ 166,254.61
1984-09-01	$ 67,914.94	$ 165,952.41
1984-10-01	$ 68,040.45	$ 165,785.44
1984-11-01	$ 68,050.60	$ 165,810.15
1984-12-01	$ 68,197.67	$ 166,168.50
1985-01-01	$ 68,432.22	$ 166,423.91
1985-02-01	$ 68,742.84	$ 166,390.75
1985-03-01	$ 69,134.61	$ 166,709.92
1985-04-01	$ 69,604.98	$ 167,059.11
1985-05-01	$ 70,137.48	$ 167,709.62
1985-06-01	$ 70,642.08	$ 168,445.25
1985-07-01	$ 71,147.95	$ 169,336.75
1985-08-01	$ 71,638.61	$ 170,188.80
1985-09-01	$ 72,102.64	$ 170,816.69
1985-10-01	$ 72,510.89	$ 171,151.72
1985-11-01	$ 72,907.73	$ 171,614.76
1985-12-01	$ 73,295.69	$ 172,054.43
1986-01-01	$ 73,735.64	$ 172,613.37
1986-02-01	$ 74,171.78	$ 174,110.95
1986-03-01	$ 74,730.90	$ 176,229.61
1986-04-01	$ 75,419.34	$ 178,180.62
1986-05-01	$ 76,136.94	$ 179,380.46
1986-06-01	$ 76,893.85	$ 180,171.07
1986-07-01	$ 77,657.10	$ 181,959.44
1986-08-01	$ 78,330.33	$ 183,202.28
1986-09-01	$ 78,912.27	$ 183,725.95
1986-10-01	$ 79,354.75	$ 184,588.64
1986-11-01	$ 79,751.59	$ 185,343.70
1986-12-01	$ 80,338.60	$ 186,538.96
1987-01-01	$ 80,829.26	$ 186,496.79
1987-02-01	$ 81,336.40	$ 186,994.27
1987-03-01	$ 81,762.40	$ 187,135.23
1987-04-01	$ 82,402.66	$ 187,596.57
1987-05-01	$ 83,131.67	$ 188,586.89
1987-06-01	$ 83,979.87	$ 189,839.63
1987-07-01	$ 84,694.93	$ 190,951.35
1987-08-01	$ 85,303.50	$ 191,314.73
1987-09-01	$ 85,753.59	$ 191,320.73
1987-10-01	$ 86,107.32	$ 191,610.07
1987-11-01	$ 86,349.48	$ 191,982.43
1987-12-01	$ 86,667.71	$ 192,689.95
1988-01-01	$ 86,968.19	$ 192,856.66
1988-02-01	$ 87,390.38	$ 193,291.71
1988-03-01	$ 87,906.40	$ 193,598.56
1988-04-01	$ 88,493.41	$ 193,892.77
1988-05-01	$ 89,278.21	$ 194,946.38
1988-06-01	$ 90,113.73	$ 195,937.02
1988-07-01	$ 90,897.26	$ 196,806.75
1988-08-01	$ 91,531.18	$ 197,346.61
1988-09-01	$ 92,024.38	$ 197,085.03
1988-10-01	$ 92,338.80	$ 197,100.32
1988-11-01	$ 92,646.89	$ 197,593.56
1988-12-01	$ 92,915.67	$ 197,837.91
1989-01-01	$ 93,342.94	$ 197,762.94
1989-02-01	$ 93,786.69	$ 197,886.05
1989-03-01	$ 94,347.08	$ 197,929.06
1989-04-01	$ 94,927.75	$ 197,853.03
1989-05-01	$ 95,471.66	$ 197,861.55
1989-06-01	$ 95,978.80	$ 198,431.72
1989-07-01	$ 96,417.48	$ 198,857.95
1989-08-01	$ 96,710.35	$ 199,141.82
1989-09-01	$ 96,897.99	$ 198,889.72
1989-10-01	$ 96,981.67	$ 198,110.54
1989-11-01	$ 97,020.97	$ 197,718.57
1989-12-01	$ 96,989.28	$ 197,340.49
1990-01-01	$ 97,024.78	$ 195,398.31
1990-02-01	$ 97,100.85	$ 194,634.86
1990-03-01	$ 97,358.22	$ 194,089.33
1990-04-01	$ 97,676.45	$ 194,421.61
1990-05-01	$ 98,003.56	$ 194,619.74
1990-06-01	$ 98,263.47	$ 194,084.34
1990-07-01	$ 98,329.40	$ 193,469.87
1990-08-01	$ 98,224.16	$ 191,500.55
1990-09-01	$ 97,905.93	$ 189,297.84
1990-10-01	$ 97,505.29	$ 187,393.49
1990-11-01	$ 96,830.80	$ 185,679.93
1990-12-01	$ 96,312.25	$ 184,685.57
1991-01-01	$ 96,112.75	$ 183,207.62
1991-02-01	$ 96,497.20	$ 183,667.54
1991-03-01	$ 96,795.15	$ 183,961.70
1991-04-01	$ 96,795.15	$ 183,689.57
1991-05-01	$ 96,948.93	$ 183,438.68
1991-06-01	$ 97,429.50	$ 183,805.76
1991-07-01	$ 97,381.44	$ 183,445.33
1991-08-01	$ 97,323.77	$ 182,799.84
1991-09-01	$ 97,429.50	$ 182,198.13
1991-10-01	$ 97,650.56	$ 182,345.72
1991-11-01	$ 98,131.12	$ 182,711.18
1991-12-01	$ 98,179.18	$ 182,668.09
1992-01-01	$ 98,275.29	$ 182,582.11
1992-02-01	$ 98,938.47	$ 183,151.10
1992-03-01	$ 99,015.36	$ 182,372.36
1992-04-01	$ 98,928.86	$ 181,951.80
1992-05-01	$ 99,111.47	$ 182,026.70
1992-06-01	$ 99,447.87	$ 181,993.14
1992-07-01	$ 99,688.15	$ 182,043.33
1992-08-01	$ 100,274.44	$ 182,594.13
1992-09-01	$ 100,505.11	$ 182,496.08
1992-10-01	$ 100,687.72	$ 182,183.00
1992-11-01	$ 100,918.39	$ 182,343.19
1992-12-01	$ 100,524.33	$ 181,759.18
1993-01-01	$ 100,264.82	$ 180,400.04
1993-02-01	$ 99,986.10	$ 179,269.97
1993-03-01	$ 100,582.00	$ 179,710.47
1993-04-01	$ 101,418.18	$ 180,701.13
1993-05-01	$ 101,744.96	$ 181,031.94
1993-06-01	$ 102,523.47	$ 182,164.48
1993-07-01	$ 102,504.25	$ 182,130.32
1993-08-01	$ 102,955.98	$ 182,427.62
1993-09-01	$ 103,157.82	$ 182,407.34
1993-10-01	$ 103,311.60	$ 181,926.98
1993-11-01	$ 103,474.99	$ 182,089.72
1993-12-01	$ 103,667.22	$ 182,427.99
1994-01-01	$ 103,590.33	$ 181,793.94
1994-02-01	$ 103,744.11	$ 181,443.28
1994-03-01	$ 104,445.73	$ 182,049.90
1994-04-01	$ 104,993.57	$ 182,756.48
1994-05-01	$ 105,522.19	$ 183,552.10
1994-06-01	$ 106,127.70	$ 183,981.69
1994-07-01	$ 106,214.20	$ 183,635.34
1994-08-01	$ 106,531.38	$ 183,442.03
1994-09-01	$ 106,406.43	$ 182,736.31
1994-10-01	$ 106,464.10	$ 182,713.04
1994-11-01	$ 106,579.43	$ 182,666.61
1994-12-01	$ 106,281.48	$ 182,155.95
1995-01-01	$ 106,339.15	$ 181,527.23
1995-02-01	$ 106,771.66	$ 181,540.83
1995-03-01	$ 107,011.94	$ 181,348.48
1995-04-01	$ 107,463.67	$ 181,514.56
1995-05-01	$ 107,838.51	$ 181,788.66
1995-06-01	$ 108,617.02	$ 182,740.84
1995-07-01	$ 109,116.81	$ 183,581.70
1995-08-01	$ 109,453.20	$ 183,665.91
1995-09-01	$ 109,366.70	$ 183,161.39
1995-10-01	$ 109,260.98	$ 182,389.06
1995-11-01	$ 109,299.42	$ 182,572.02
1995-12-01	$ 109,433.98	$ 182,915.87
1996-01-01	$ 109,530.09	$ 182,009.36
1996-02-01	$ 109,683.87	$ 181,676.57
1996-03-01	$ 110,443.17	$ 181,994.31
1996-04-01	$ 111,029.45	$ 182,258.08
1996-05-01	$ 111,606.13	$ 182,853.74
1996-06-01	$ 112,096.30	$ 183,539.64
1996-07-01	$ 112,499.98	$ 183,848.61
1996-08-01	$ 112,499.98	$ 183,497.98
1996-09-01	$ 112,442.31	$ 182,822.79
1996-10-01	$ 112,307.75	$ 182,027.24
1996-11-01	$ 112,442.31	$ 181,900.61
1996-12-01	$ 112,413.48	$ 181,853.96
1997-01-01	$ 112,288.53	$ 181,080.96
1997-02-01	$ 112,538.42	$ 180,915.39
1997-03-01	$ 113,461.11	$ 181,942.68
1997-04-01	$ 113,960.89	$ 182,515.98
1997-05-01	$ 114,768.24	$ 183,923.81
1997-06-01	$ 115,191.14	$ 184,371.21
1997-07-01	$ 115,498.70	$ 184,633.12
1997-08-01	$ 115,863.92	$ 184,871.41
1997-09-01	$ 115,642.87	$ 184,060.83
1997-10-01	$ 116,017.71	$ 184,200.36
1997-11-01	$ 116,171.49	$ 184,558.73
1997-12-01	$ 116,238.76	$ 184,894.58
1998-01-01	$ 116,354.10	$ 184,734.45
1998-02-01	$ 117,199.89	$ 185,732.51
1998-03-01	$ 118,045.68	$ 186,726.88
1998-04-01	$ 118,920.31	$ 187,763.10
1998-05-01	$ 119,794.94	$ 188,795.50
1998-06-01	$ 120,957.90	$ 190,394.41
1998-07-01	$ 121,198.18	$ 190,538.84
1998-08-01	$ 121,688.36	$ 191,075.30
1998-09-01	$ 122,120.87	$ 191,520.00
1998-10-01	$ 122,370.76	$ 191,443.83
1998-11-01	$ 122,908.99	$ 192,285.87
1998-12-01	$ 123,101.22	$ 192,704.10
1999-01-01	$ 123,552.95	$ 192,940.37
1999-02-01	$ 124,052.73	$ 193,485.31
1999-03-01	$ 125,042.69	$ 194,438.36
1999-04-01	$ 126,003.82	$ 194,518.21
1999-05-01	$ 127,195.62	$ 196,358.04
1999-06-01	$ 128,224.02	$ 197,945.65
1999-07-01	$ 128,858.37	$ 198,328.26
1999-08-01	$ 129,579.21	$ 198,960.32
1999-09-01	$ 129,627.27	$ 198,085.76
1999-10-01	$ 130,203.95	$ 198,612.11
1999-11-01	$ 130,376.95	$ 198,757.84
1999-12-01	$ 130,626.84	$ 199,138.80
2000-01-01	$ 131,905.14	$ 200,491.91
2000-02-01	$ 131,712.92	$ 199,020.70
2000-03-01	$ 133,221.89	$ 199,654.63
2000-04-01	$ 134,461.74	$ 201,395.12
2000-05-01	$ 135,557.43	$ 202,799.45
2000-06-01	$ 136,931.84	$ 203,786.19
2000-07-01	$ 137,623.85	$ 204,341.95
2000-08-01	$ 138,037.14	$ 204,955.59
2000-09-01	$ 138,642.65	$ 204,788.04
2000-10-01	$ 139,094.38	$ 205,101.05
2000-11-01	$ 139,526.88	$ 205,620.63
2000-12-01	$ 139,920.95	$ 206,319.87
2001-01-01	$ 140,574.51	$ 205,981.40
2001-02-01	$ 141,487.58	$ 206,493.81
2001-03-01	$ 142,756.27	$ 207,872.42
2001-04-01	$ 143,957.68	$ 208,792.35
2001-05-01	$ 145,159.09	$ 209,587.02
2001-06-01	$ 146,360.50	$ 210,965.51
2001-07-01	$ 147,177.46	$ 212,740.67
2001-08-01	$ 147,754.14	$ 213,574.23
2001-09-01	$ 148,253.92	$ 213,335.15
2001-10-01	$ 148,830.60	$ 214,888.10
2001-11-01	$ 148,811.38	$ 215,223.70
2001-12-01	$ 149,320.77	$ 216,815.96
2002-01-01	$ 149,839.78	$ 217,078.17
2002-02-01	$ 150,695.19	$ 217,457.90
2002-03-01	$ 152,194.55	$ 218,393.21
2002-04-01	$ 153,453.62	$ 218,975.25
2002-05-01	$ 155,106.76	$ 221,334.24
2002-06-01	$ 156,615.73	$ 223,363.29
2002-07-01	$ 157,644.14	$ 224,580.31
2002-08-01	$ 158,499.54	$ 225,049.18
2002-09-01	$ 159,230.00	$ 225,711.60
2002-10-01	$ 159,931.62	$ 226,331.03
2002-11-01	$ 160,287.24	$ 226,834.29
2002-12-01	$ 160,950.42	$ 228,276.45
2003-01-01	$ 161,498.26	$ 228,044.96
2003-02-01	$ 162,545.89	$ 227,769.31
2003-03-01	$ 163,670.41	$ 227,975.46
2003-04-01	$ 165,179.38	$ 230,578.01
2003-05-01	$ 166,803.68	$ 233,226.09
2003-06-01	$ 168,178.10	$ 234,891.79
2003-07-01	$ 169,437.17	$ 236,392.96
2003-08-01	$ 170,542.47	$ 237,032.79
2003-09-01	$ 171,638.16	$ 237,782.79
2003-10-01	$ 172,176.39	$ 238,786.31
2003-11-01	$ 172,916.46	$ 240,462.59
2003-12-01	$ 173,791.08	$ 241,941.14
2004-01-01	$ 174,348.54	$ 241,537.68
2004-02-01	$ 175,771.00	$ 242,200.55
2004-03-01	$ 177,683.65	$ 243,268.26
2004-04-01	$ 179,778.91	$ 245,351.35
2004-05-01	$ 182,364.34	$ 247,432.05
2004-06-01	$ 184,824.83	$ 249,977.28
2004-07-01	$ 186,362.63	$ 252,456.42
2004-08-01	$ 187,564.04	$ 253,949.83
2004-09-01	$ 188,630.89	$ 254,856.33
2004-10-01	$ 189,457.46	$ 254,632.22
2004-11-01	$ 190,505.09	$ 255,906.18
2004-12-01	$ 191,446.99	$ 258,117.43
2005-01-01	$ 192,129.39	$ 258,494.13
2005-02-01	$ 193,782.53	$ 259,223.04
2005-03-01	$ 196,589.03	$ 260,936.59
2005-04-01	$ 199,020.68	$ 262,399.46
2005-05-01	$ 201,615.72	$ 266,094.38
2005-06-01	$ 204,085.82	$ 269,215.96
2005-07-01	$ 205,950.41	$ 270,424.27
2005-08-01	$ 207,411.32	$ 270,955.86
2005-09-01	$ 208,804.96	$ 269,483.38
2005-10-01	$ 209,285.52	$ 269,561.22
2005-11-01	$ 209,862.20	$ 272,492.68
2005-12-01	$ 210,227.43	$ 274,076.53
2006-01-01	$ 210,794.49	$ 272,737.03
2006-02-01	$ 211,717.17	$ 273,379.40
2006-03-01	$ 213,303.03	$ 273,910.78
2006-04-01	$ 214,667.84	$ 273,337.67
2006-05-01	$ 216,407.48	$ 274,192.01
2006-06-01	$ 217,118.71	$ 274,550.84
2006-07-01	$ 216,878.43	$ 273,438.41
2006-08-01	$ 217,378.22	$ 273,530.88
2006-09-01	$ 216,647.76	$ 273,955.31
2006-10-01	$ 216,272.92	$ 274,972.05
2006-11-01	$ 216,003.80	$ 275,038.77
2006-12-01	$ 215,167.62	$ 273,566.76
2007-01-01	$ 214,956.17	$ 272,466.21
2007-02-01	$ 215,667.41	$ 271,912.90
2007-03-01	$ 217,378.22	$ 271,596.80
2007-04-01	$ 218,473.90	$ 271,203.99
2007-05-01	$ 218,714.18	$ 269,853.26
2007-06-01	$ 218,723.79	$ 269,343.14
2007-07-01	$ 217,464.72	$ 267,860.81
2007-08-01	$ 216,292.14	$ 266,905.98
2007-09-01	$ 214,629.39	$ 264,126.23
2007-10-01	$ 212,370.74	$ 260,788.82
2007-11-01	$ 210,064.03	$ 256,433.10
2007-12-01	$ 207,911.11	$ 253,975.32
2008-01-01	$ 205,114.23	$ 249,319.51
2008-02-01	$ 204,489.50	$ 247,840.38
2008-03-01	$ 203,374.59	$ 244,370.86
2008-04-01	$ 202,394.24	$ 241,726.87
2008-05-01	$ 201,471.55	$ 238,615.52
2008-06-01	$ 201,019.82	$ 235,705.31
2008-07-01	$ 198,991.85	$ 232,108.60
2008-08-01	$ 196,752.42	$ 230,416.21
2008-09-01	$ 194,263.10	$ 227,816.04
2008-10-01	$ 192,119.78	$ 227,601.62
2008-11-01	$ 187,900.43	$ 226,949.76
2008-12-01	$ 186,237.68	$ 227,292.22
2009-01-01	$ 186,977.75	$ 227,206.53
2009-02-01	$ 187,813.93	$ 227,093.30
2009-03-01	$ 186,035.85	$ 224,397.67
2009-04-01	$ 186,333.80	$ 224,197.38
2009-05-01	$ 187,477.54	$ 224,923.78
2009-06-01	$ 188,198.38	$ 223,865.62
2009-07-01	$ 187,515.98	$ 223,408.13
2009-08-01	$ 186,766.30	$ 222,017.00
2009-09-01	$ 185,824.40	$ 220,759.24
2009-10-01	$ 185,757.12	$ 220,466.98
2009-11-01	$ 185,536.06	$ 220,048.87
2009-12-01	$ 182,364.34	$ 216,668.75
2010-01-01	$ 181,547.38	$ 214,963.49
2010-02-01	$ 181,143.71	$ 214,432.07
2010-03-01	$ 181,681.94	$ 214,189.69
2010-04-01	$ 183,354.30	$ 215,786.49
2010-05-01	$ 184,988.22	$ 217,540.78
2010-06-01	$ 184,046.31	$ 216,644.63
2010-07-01	$ 182,691.12	$ 215,004.03
2010-08-01	$ 182,133.67	$ 214,052.45
2010-09-01	$ 179,471.35	$ 210,800.92
2010-10-01	$ 179,211.84	$ 210,234.33
2010-11-01	$ 177,943.15	$ 208,658.26
2010-12-01	$ 175,194.33	$ 205,082.53
2011-01-01	$ 173,406.63	$ 202,027.55
2011-02-01	$ 171,811.16	$ 199,186.48
2011-03-01	$ 170,974.98	$ 196,302.90
2011-04-01	$ 172,762.68	$ 197,086.30
2011-05-01	$ 173,954.47	$ 197,516.74
2011-06-01	$ 175,665.28	$ 199,673.12
2011-07-01	$ 176,030.51	$ 199,911.14
2011-08-01	$ 174,819.49	$ 197,989.85
2011-09-01	$ 175,021.32	$ 197,917.91
2011-10-01	$ 173,368.19	$ 196,453.72
2011-11-01	$ 173,608.47	$ 196,892.09
2011-12-01	$ 172,733.84	$ 196,384.55
2012-01-01	$ 171,215.26	$ 193,805.27
2012-02-01	$ 171,474.76	$ 193,248.14
2012-03-01	$ 174,108.25	$ 194,737.08
2012-04-01	$ 176,578.35	$ 196,904.99
2012-05-01	$ 179,480.96	$ 200,376.86
2012-06-01	$ 181,316.71	$ 202,723.61
2012-07-01	$ 181,672.33	$ 203,452.80
2012-08-01	$ 181,979.89	$ 202,669.35
2012-09-01	$ 181,633.88	$ 201,385.38
2012-10-01	$ 181,835.72	$ 201,687.61
2012-11-01	$ 182,133.67	$ 202,979.82
2012-12-01	$ 181,681.94	$ 203,023.14
2013-01-01	$ 181,864.55	$ 202,627.98
2013-02-01	$ 183,123.63	$ 202,373.36
2013-03-01	$ 186,391.46	$ 205,447.56
2013-04-01	$ 189,024.95	$ 208,567.12
2013-05-01	$ 192,456.18	$ 211,975.68
2013-06-01	$ 194,762.88	$ 214,002.79
2013-07-01	$ 195,858.57	$ 215,121.96
2013-08-01	$ 195,454.90	$ 214,420.65
2013-09-01	$ 195,416.45	$ 214,129.44
2013-10-01	$ 194,955.11	$ 214,175.48
2013-11-01	$ 194,532.21	$ 214,148.28
2013-12-01	$ 194,061.26	$ 213,648.17
2014-01-01	$ 193,763.31	$ 212,529.48
2014-02-01	$ 194,820.55	$ 212,901.83
2014-03-01	$ 197,223.37	$ 214,148.53
2014-04-01	$ 199,501.24	$ 215,910.08
2014-05-01	$ 201,683.00	$ 217,511.60
2014-06-01	$ 203,864.76	$ 219,455.93
2014-07-01	$ 204,566.39	$ 220,297.18
2014-08-01	$ 204,489.50	$ 220,582.86
2014-09-01	$ 203,537.98	$ 219,391.35
2014-10-01	$ 203,778.26	$ 220,203.56
2014-11-01	$ 203,970.49	$ 221,607.83
2014-12-01	$ 204,037.77	$ 222,945.05
2015-01-01	$ 202,999.75	$ 222,859.60
2015-02-01	$ 204,864.33	$ 223,934.05
2015-03-01	$ 207,584.33	$ 225,564.73
2015-04-01	$ 209,794.92	$ 227,504.31
2015-05-01	$ 212,832.08	$ 229,627.38
2015-06-01	$ 214,840.84	$ 230,985.55
2015-07-01	$ 215,715.46	$ 231,910.35
2015-08-01	$ 215,004.23	$ 231,473.55
2015-09-01	$ 215,206.07	$ 232,052.10
2015-10-01	$ 215,186.84	$ 232,135.76
2015-11-01	$ 215,734.69	$ 233,219.00
2015-12-01	$ 215,379.07	$ 233,632.91
2016-01-01	$ 215,407.90	$ 233,278.55
2016-02-01	$ 216,253.70	$ 234,001.91
2016-03-01	$ 219,732.98	$ 236,747.31
2016-04-01	$ 222,183.85	$ 238,258.36
2016-05-01	$ 224,971.12	$ 240,275.18
2016-06-01	$ 227,008.71	$ 241,657.69
2016-07-01	$ 228,056.34	$ 243,166.40
2016-08-01	$ 228,114.01	$ 243,004.70
2016-09-01	$ 228,431.18	$ 242,758.99
2016-10-01	$ 228,479.24	$ 242,507.71
2016-11-01	$ 229,180.86	$ 243,631.37
2016-12-01	$ 228,979.02	$ 243,337.16
2017-01-01	$ 227,854.51	$ 240,739.17
2017-02-01	$ 230,420.72	$ 242,686.97
2017-03-01	$ 233,803.89	$ 246,050.25
2017-04-01	$ 237,033.27	$ 248,711.23
2017-05-01	$ 239,820.54	$ 251,420.92
2017-06-01	$ 241,387.18	$ 252,833.99
2017-07-01	$ 242,800.04	$ 254,489.43
2017-08-01	$ 243,607.39	$ 254,573.33
2017-09-01	$ 243,472.83	$ 253,092.62
2017-10-01	$ 243,818.83	$ 253,612.59
2017-11-01	$ 244,635.79	$ 254,456.17
2017-12-01	$ 244,309.01	$ 254,265.74
2018-01-01	$ 244,943.35	$ 253,544.69
2018-02-01	$ 247,807.51	$ 255,351.48
2018-03-01	$ 250,748.56	$ 257,799.15
2018-04-01	$ 253,132.16	$ 259,219.35
2018-05-01	$ 256,034.76	$ 261,105.84
2018-06-01	$ 257,937.80	$ 262,627.97
2018-07-01	$ 258,927.76	$ 263,618.14
2018-08-01	$ 259,264.15	$ 263,814.07
2018-09-01	$ 258,975.82	$ 263,214.81
2018-10-01	$ 258,870.09	$ 262,643.33
2018-11-01	$ 259,331.43	$ 263,995.61
2018-12-01	$ 258,946.98	$ 264,448.88
2019-01-01	$ 259,168.04	$ 264,170.97
2019-02-01	$ 260,926.90	$ 264,844.28
2019-03-01	$ 264,050.57	$ 266,511.35
2019-04-01	$ 266,943.56	$ 268,012.18
2019-05-01	$ 269,567.44	$ 270,071.65
2019-06-01	$ 270,576.62	$ 271,028.74
2019-07-01	$ 271,768.42	$ 271,768.42

Methodology on US Historical Home Prices

For this historical data, I mashed up a few sets (and used a couple proxies) to show you these median home prices.

The NAR has a restrictive sharing license for non-REALTOR®s (like yours truly). We can use the data only if we also substantially transform it; we’ll do that by sampling over a year.

First, take the overlap of the NAR’s data and the FHFA index to come up with an average “multiple.” For the first revision of this post, that was a 12-month overlap and a 961.13 average multiple.

Second, use the average ratio in the overlap of the FHFA index and Shiller’s NSA home data. That averaged to 1.319 over 337 samples.

Finally, for data back to 1991, multiply the FHFA index by 961.13. Between 1953 and 1991, multiple by (961.13*1.319).

If you want to adjust for inflation, I used NSA CPI-U. It’s a bit dubious (CPI-U includes shelter), but should do a decent job of showing price level. Use the raw data and your favorite deflator if you’re hardcore.

How do I cite this data?

Credit Don’t Quit Your Day Job… and link back to this page. Note the underlying sources, too (The National Association of Realtors, The Federal Housing Finance Agency, Robert Shiller, and the U.S. Bureau of Labor Statistics).

Can you get US median home price data before 1953?

Yes, but maybe not monthly median home values.

Shiller’s monthly data started in 1953; before then, we have a yearly home value resolution. If you clamor enough, I’ll extend the series further back with linear interpolation (and ironically, by adding some seasonality).

Why are you deriving historical median home values and not average?

Home prices have an extensive span, and there are some wildly expensive properties in the United States. They sell rarely… rarely enough that median is a better representation of home sales than average.

Why look at single-family home prices?

Some of it is personal interest, and my sense of what the “American Dream” might be (or was, as the case may be).

I don’t know the condo, co-op, townhome, or multi-family market well enough to try to create proxies. Single-family homes are mostly comparable countrywide, so this feels like a good series.

Is this data reasonable?

Yes, arguably.

In a sense, looking at home-price data for a country as large as the United States is weird on its face.

Small local markets are mostly blended away. Still, if California, Texas, or New York change housing policies, it can move the whole country’s median home price.

So, it’s about as reasonable as looking at any US-aggregate data. I trust the underlying indices to get us in the ballpark of the actual market, too.

Consider: we look at recessions on a country-level, but also recognize that some regions or industries might be in contraction while others are expanding.

Apply the same skepticism to this aggregated data as you do other aggregates.

United States Home Price History

Median home prices were an interesting data set to proxy. I’ll soon be mashing it up with other long-term values (such as the mortgage rate) for a few posts on the housing market.

One thing I noted is how much the market has changed since around 1998.

The Great Recession’s bottom in 2009 only took inflation-adjusted home prices back to the peak of 1991. From the (admittedly limited) data, we’re in outlier times right now – only matched by the recent peak in 2006.

Let me know if you have any theories, requests, or comments in the… comments.

FFMI Calculator (Fat-Free Mass Index)

Health September 3, 2019 by PK

On this page is a FFMI Calculator. FFMI, or Fat Free Mass Index, factors in a person’s body fat percentage, height, and weight to arrive at a lean mass ratio.

Using that number you can compare your relative muscularity versus benchmarks for large populations of men and women.

Fat Free Mass Index Calculator

What is FFMI?

FFMI, or Fat Free Mass Index is a measurement of your lean mass compared to your height. As opposed to other measures like BMI (body mass index), FFMI takes your muscularity into consideration, and is better suited to athletes and people who work out.

Lean mass isn’t just muscularity, however.

Lean mass is everything in your body that isn’t fat: muscles, water, undigested food, organs, bones, and so on. Of course, those don’t actually change too much for a typical male or female with two exceptions:

Height: Taller people have larger organs and bones. The basic FFMI formula doesn’t fully account for this – in ‘Adjusted FFMI’ below, the equation normalizes FFMI to a 5’11” male.
Weight: If you have a higher body fat percentage you can support higher musculature…. up to a point. When you diet without steroids or other artificial help, you’ll lose muscle as well as fat. The benchmarks below apply to people with under 10% body fat.

FFMI Formula

To calculate your FFMI, there is a two-step process… assuming you know your body fat percentage (Estimate it from your waist and height measurements. Use the caliper reading from the tool.).

Calculate your lean weight (in kilograms):
Total Weight * (100% – Body Fat) = Lean Weight (kg)
Divide your Lean Weight by your Height (in meters), squared

FFMI = Lean Weight (kg) / (Height (m) * Height (m))

Normalized FFMI Formula

Since height does affect FFMI and the original 1995 FFMI study from Elena Kouri Ph.D., Harrison Pope Jr. M.D., David Katz M.D., J.D. and Paul Oliva B.A. wanted to better isolate muscle, they also proposed a normalized FFMI formula.

The normalized FFMI formula adjusts the FFMI reading from the above for a 1.8 meter tall (5′ 10.87″) male:

Normalized FFMI = FFMI + (6.1 * (1.8 – Height (m) ) )

Natural Muscle Limit vs. FFMI

Testosterone, a naturally occurring anabolic steroid was first isolated in 1935. Steroids were used in clinical trials shortly thereafter, and were almost certainly part of German and Allied military experiments during World War II.

I tell you this because steroids almost certainly entered athletics shortly after.

And (of course) steroids are pervasive today. In every sport you can assume that the vast majority of top athletes have some sort of chemical assistance.

I’m not judging. I’m just saying that if you are lifting at the gym and have no interest in steroids, taking hints from muscle magazine covers or athletes on TV isn’t realistic.

No matter how perfect your diet, sleep, vitamin regimen, and workout routine – your maximum muscle weight won’t be close to the players you see on TV.

How big can you get without steroids?

In Kouri et. al’s original paper on FFMI, they theorized that all bodybuilders who won the Mr. America bodybuilding competition after 1960 are suspect.

They took height, weight, and bodyfat percentage estimates for all the winners before 1960 and estimated normalized FFMIs:

FFMI estimates of early Mr. America Winners.
Kouri EM1, Pope HG Jr, Katz DL, Oliva P., *Fat-free mass index in users and nonusers of anabolic-androgenic steroids.*

You’ll note that the average Mr. America winner clocked in at around an FFMI of 25 (25.4 to be exact). The “non-steroid” winners ranged between Roland Essmaker’s winning 22.6 FFMI in 1939 and Jack Delinger‘s huge FFMI of 28.0 in 1949.

You probably note the timeline too. If the first steroid was isolated in 1935, potentially everyone above had chemical assistance. It’s hard to believe that after World War II – with various armies experimenting – that steroids didn’t factor into the contests from 1946-1960.

(Also, what was John Grimek’s 1940 off-season like?)

Anyway, let’s take the early winners at their word. If Mr. America winners have both superior genetics and come close to perfect with diet and workouts they are a good benchmark for what “might” be possible without steroids.

(Probable) Genetic Max Musculature Based on FFMI

If you are a male and don’t take steroids:

22-23: Likely attainable
24-25: Possible
26-28: Theoretically possible (but suspect)

Of course, your own natural build and genetics enter into play. You can always increase your FFMI from your baseline, but a slender male might only make it to 20 or 21 FFMI.

Man with strong back — A “drop” (ratio of chest to waist) like this requires low body fat and an FFMI of 22-25+

FFMI Benchmarks for Men and Women

Of course, you can go higher than an FFMI of 26-28.

But – other than the absolute top fraction of a percent of athletes (e.g. champion powerlifter Ray Williams) – a higher number will require steroids. Before you choose that path (no judgement!) take a look at what the FFMI scale looks like.

Note that these benchmarks don’t account for body fat percentage. If you are dieting but do not have abs yet, expect lower FFMI as you target lower body fat. And if you have a higher body fat percentage note it makes your muscle look softer.

FFMI Benchmarks for Men

<17: Very low muscle, skinny, “scrawny”
17-20: Average male, probably doesn’t lift weights
20-21: Obviously lifts
21-23: Very well-built
23-25: Extremely muscular
25-28: Superior musculature , “juicy” (and likely not drug-free)
28+: With few exceptions, only attainable with steroids, growth hormone, and/or SARMs

FFMI Benchmarks for Women

<14: Very low muscle
14-16: Average female, likely doesn’t lift weights
16-18: Athletic woman
18-19: Very well-built
19-21: Extremely muscular
20-21+: Hard to obtain without steroids, growth hormone, and/or SARMs

Usefulness of FFMI

FFMI is a useful measure of body composition for both men and women.

It factors in body fat percentage, height, and weight in a smart, normalized way. Importantly, it’s an improvement on BMI – which doesn’t account for people with above or below average musculature.

FFMI is also useful as a guess of what’s possible if you dedicate yourself to drug-free diet and exercise. If you have a slender build (like me), you will likely top out on the lower end of the range. If you are naturally a bit larger, with proper diet, sleep, and exercise you can push 25 or even higher in FFMI.

(For what it’s worth, I’m right around an FFMI of 23. I would likely be ~18 without lifting.)

Does Dollar Cost Averaging Work? How Should You Use It?

Investing August 25, 2019 by PK

Dollar Cost Averaging is a set it and forget it investment strategy that lines up well with how your paycheck works. You’re paid on a periodic basis, and if you use DCA… you turn right around and invest on a periodic basis too.

Today I’ll talk about what dollar cost averaging is, how you should use it, and answer the burning question: does dollar cost averaging work?

What is Dollar Cost Averaging?

Dollar Cost Averaging is a strategy where you invest money into the same investments on a regular basis. You make those purchases without even looking at the price – again, dollar cost averaging is a set it and forget it investing strategy.

Investments rise and fall in value all the time. This means that you’ll buy more of an investment while the price is low and less while the price is high.

On average, though, using DCA you’ll get a middling price – which tends to increase over time.

Benefits of Dollar Cost Averaging

There are quite a few benefits of dollar cost averaging, even beyond your investment in the stock market.

Here are a few benefits of dollar cost averaging:

Reduces cognitive load: Most of you – even if you work in finance – have better things to do than pick stocks every 2 weeks.

Dollar cost averaging lets you set an investment up front and automate it. Then you only need to look at your plan at a scheduled time annually.
Avoids timing the market: Even if you are a very good investor, it’s extremely hard (and others will say impossible) to time the market.

Dollar Cost Averaging just plows ahead mechanically no matter the market conditions. You’ll win some and you’ll lose some, but it’ll all average out over time.
Removes emotions from investing: If your money is on autopilot through a dollar cost averaging plan, you don’t have to worry about your emotions getting in the way of making investments.

You know you should invest, but it can be hard when you’re fearful. If your DCA plan is still running, you don’t have to worry – you’ll buy the lows, highs, and everything in between.

Are There Drawbacks to Dollar Cost Averaging?

Alas, there are some downsides to dollar cost averaging. But: they are mostly avoidable (with the possible exception of management costs inside your 401(k))

Let’s look at how to avoid dollar cost averaging pitfalls.

Avoid Costs when Dollar Cost Averaging

The first trap in dollar cost averaging is cost. Costs mainly appear through transaction costs or investment costs (such as management fees).

When you buy stocks or ETFs through most brokerage accounts, you have to pay a commission.

Commissions vary per brokerage, but assume for most brokerages it’s somewhere between $5 and $100. It depends on factors such as whether you buy online or dial into a company to trade.

Those fees up quickly – especially if you average into multiple stocks or ETFs. And if you purchase mutual funds they might have a load which acts much like a commission.

You also have to watch for management fees.

ETFs and mutual funds come with management costs, and not all funds are created equal. You should look for low cost, no-load mutual funds and ETFs for your DCA plan. And if you only have high cost funds inside your 401(k), you need to appeal to your company to add better options.

Bottom Line: Dollar Cost Averaging is easiest with a no-load mutual fund. Alternatively for ETFs and stocks, look for a broker that has free trades. (Or invest in stocks which have free “Direct Reinvestment Plans” – also called DRIP plans).

Avoid Underperforming Versus Lump Sum Investing

I wrote about how lump sum investing is better for a windfall. That post holds up – if you receive a lump sum, you should generally invest it all at once.

However, there is negative benefit to saving up in order to invest a lump sum. The positive drift of the stock market works against you if you’re out of the market.

Bottom Line: Unless you have foresight the market is about to drop, you will lose if you save your paychecks to make a later lump sum purchase.

How to Dollar Cost Average

Convinced that dollar cost averaging is the right everyday (well… every two week?) investment strategy?

Good – it’s simple to get things going:

Set your target asset allocation for your DCA funds (for example, 80% stock 20% bonds)
- Revisit this on a periodic basis; perhaps once a year. Resist the urge to change too often.
Apply your allocation across all your accounts where you DCA
- For example, set your allocation across your 401(k) and an IRA
Automatically send money to your accounts
- For some accounts (such as your 401(k)) you can push money automatically. For other accounts such as an IRA or 529, you might need to deposit your paycheck in a bank account first then pull money.
That’s it. Go back to step 1 once a year or so.

Set up your dollar cost averaging. Evaluate once a year. Profit 📈

Does Dollar Cost Averaging Work?

The subtext here is: “will I make money from dollar cost averaging?”.

And the answer? Almost certainly, yes. Dollar cost averaging works over time.

The few scenarios where the answer is no involve population collapse, famine, war and other societal issues. In these pessimistic situations you have bigger problems than your retirement portfolio, however.

So, back to yes.

You’re on Don’t Quit Your Day Job… I’ll prove it to you.

These next few calculators have periodic investing features. Using your own choice of inputs, you can see the effect of continuous investments into something:

*We don’t – yet – have a mutual fund return calculator

Please use a long enough time period in your scenario. Dollar Cost Averaging is a strategy you employ over a career, not a few paychecks.

Dollar Cost Averaging Worked in the United States. What About Japan?

It’s true – Japan’s stock markets have been range-bound for a ridiculously long time. And since World War II Japan has had a relatively strong economy and avoided wars.

However, the stock market hasn’t collapsed entirely. It’s just that Nikkei lump sum investments in the 1980s have failed to keep up with inflation.

If you started your career in Japan in the late 1980s and continued to periodically invest, you would have also invested after the fall. You didn’t perform as well as investors in the United States, but dollar cost averaging is viable even in Japan.

In Conclusion: You Should Dollar Cost Average Where You Can

You probably see a fair number of lump sums annually.

RSUs, ESPPs, bonuses, tax returns, asset sales, and (sadly) inheritances will all leave you with windfalls and require a different investment strategy.

But for your own peace of mind, the majority of your investing should be automatic. Wherever possible, plan your investing once a year – in advance – and put it on autopilot using dollar cost averaging.

And I’m not a hypocrite here.

I max my 401(k) annually, and time it to finish in December (to catch the full match). I send funds to my daughters’ 529s twice a month, and once a month send money to a brokerage and a couple roboadvisor accounts.

I’d rather talk about efficiency here with you all than worry about where to put my money every two weeks. Even if DCA doesn’t cover my entire investing strategy.

And don’t you enjoy our time together? Let me know how you employ dollar cost averaging in the comments.

The 10 year-2 year Yield Curve Inverted 8/14/2019: What Does the Yield Curve Tell Us?

Investing August 17, 2019 by PK

On 8/14/2019, briefly, 2 year Treasuries paid slightly better than 10 year Treasuries: 1.628% vs. 1.619%.

By day’s end this brief inversion corrected, and the two yields settled at 1.58% and 1.59% respectively. Still, you can’t un-ring that bell: regardless of the closing price, we witnessed the first 10 year – 2 year inversion since we “un-inverted” in June of 2017.

Of course, you’re probably asking: what does the yield curve tell us? Why should the yield curve naturally slope upwards? And of course… what happens from here?

We’ll do our best to answer, and link you some other recent posts. Let’s party like it’s 2007 and talk yield curves.

What is a Yield Curve?

A yield curve is a plot of any comparable form of debt with yield on the Y-Axis and time on the X-Axis. Most commonly, yield curve refers to the government yield curve in your home country.

If you don’t hear modifiers assume the yield curve refers to government debt in the United States. However, know that “yield curve” isn’t an exclusive term; if a company issued bonds with various time and yield to maturity you could talk about a company’s yield curve.

Furthermore, yield curve is often shorthand for other measures. In the United States, when people talk about the yield curve offhand they usually mean the difference between the 10 year yield and either the 2 year yield or 3 month yield.

What does the yield curve tell us? One indicator: difference between US 10 Year and 2 Year Treasury yields — The difference between 10 Year and 2 Year Treasury yields in the United States

Why does the yield curve naturally slope upwards?

If people are perfectly neutral on the economy over the long term, then the yield curve will slope up and to the right. That is, as you increase the time to maturity on bonds and Treasuries the yield would be higher.

All else being equal, it’s easier to predict the very near term future than further out.

Take the US yield curve: you probably have a better idea of the next three months than the next thirty years. Who knows what the economy and political climate will look like in thirty years?

If you demand a baseline amount plus a finger-in-the-air multiplier for uncertainty, uncertainty goes up as you move further out along the curve.

So, an inverted yield curve – or even a flattening yield curve(!) – means people are less bullish on the economy in the near term than further out. Their weight to economic performance is even beating the fuzziness of the future – not a great sign.

Inverted Yield Curves and Business Plans

We (the royal we) talk about the yield curve as a recession indicator. Truthfully, the yield curve might be even more than a harbinger; the slope of the curve itself affects some business models.

We talked above about company yields – let’s discuss banks. Banks can borrow in the short term at or around the Federal Funds Rate. Long-term, they lend at a prevailing market rate – think mortgages, student loans, personal loans, business loans, and other long term debt.

Now, you and I can’t borrow for 10 years at the same rate as the Treasury. However, if the premium between what citizens and businesses can borrow at market rates isn’t high enough over the short term rate, what happens?

Well… then everything has to go perfectly for banks to make money. If any part of the model is wrong (say, more people default on mortgages than expected) banks will feel it.

And that’s one mechanism for how the yield curve can both predict a recession… and accelerate one.

How does the Federal Reserve affect the yield curve?

The Federal Reserve primarily affects the shorter end of the yield curve. Since the Fed sets overnight lending rates to depository institutions (the Federal Funds Rate), ‘1 day’ rates directly relate to the Fed’s moves.

The Fed affects the longer end too through open market operations. The Fed can use proceeds from selling (or issuing) short-term Government Securities and buying longer dated Treasuries – for example, 10, 20, or 30 years out.

The Fed’s buying pressure increases the price of the longer-dated debt. When Treasury prices increase, yields fall – and vice versa. The Fed has operationalized this multiple times, most recently in the so-called “QE2” program.

Through these mechanisms – and truthfully, the implications of having these mechanisms available – the Fed can affect the yield curve at any point.

Why Does the Yield Curve Tend to Invert Before a Recession? What Does the Yield Curve Tell Us?

All of the things we just discussed lead us to what does it mean?

Well, let’s clear something up first. A yield curve doesn’t mean that a recession is on our doorstep – note that the yield curve sometimes inverts and corrects without a recession (see: early 2006 then the quick rebound). Further, the yield curve didn’t invert at all for an entire generation after the 1920s… and we still had recessions.

But linking to everything we said above, it’s still a worrisome sign. But maybe “this time is different” (a phrase which means you should immediately be skeptical!).

One plausible scenario: the Federal Reserve might take the yield curve more seriously this time. In the below graph, you can see that since the 1990s the Fed has continued to raise rates – or keep them flat – even as the 10s2s yield curve flattened and inverted.

Yield Curve for 10s-2s versus the Effective Federal Funds Rate. — United States recent yield curve inversions and Federal Reserve reactions.

Red: Effective Federal Funds Rate,
Blue: 10 Year Treasury minus 2-Year Treasury (negative = inverted),
Grey bar: Recession

Again, Fed mistake or not, an inversion is not a good sign:

The normal shape of the yield curve with constant economic confidence is upwardly sloped
An inverted yield curve most likely means lack of confidence in the short term versus the long term
Some business models literally rely on an upward slope in the yield curve

At the end of the day, it’s true: inverted yield curves often lead recessions.

Since the 1960s, a yield curve inversion in the 10 year – 3 month or 10 year – 2 year has preceded a recession by roughly 1-2 years. It doesn’t really matter which of the two you pick, but watching the 3 month – 10 year is a little better than the widely watched 2 year – 10 year.

So, the briefly inverted 10s2s yields is a terrible sign. The continued inversion on other durations is also a bad sign. The longer the inversion continues, the harder it is to avoid a recession or other dip in economic output.

But optimistically, maybe this time really is different. Personally, though, I wouldn’t count on it – I’m taking the indicator as real… but not panicking. How about you?

How Does an Interest Rate Cut Affect the Stock Market?

Investing August 11, 2019 by PK

During their July meeting, the Federal Open Market Committee chose to lower the target Federal Funds Rate to 2% – 2.25% from 2.25% – 2.5%.

While the financial press implied this was bullish for stocks, the S&P 500 immediately fell on the news (and Fed commentary). Further, the yield curve remains inverted – or has even become more inverted – in the wake of the news.

With all of the bullish commentary around rate cuts… including from the President himself… you’d be forgiven for thinking rate cuts are bullish. So, how does an interest rate cut affect the stock market?

What is the Federal Funds Rate?

Quite simply, the Federal Funds Rate is the interest rate at which depository institutions (mostly credit unions and banks) lend their reserve funds to other depository institutions.

Importantly, it’s a short term rate – overnight and uncollateralized. That is, it’s what banks charge other banks to borrow on an immediate basis.

How Does the Federal Reserve Affect the Federal Funds Rate?

Depository institutions are required to hold reserve funds according to the amount of deposits they house from their customers. These reserve funds are the minimum they must keep on hold with the Fed in the form of cash at the bank or (alternatively) deposits at one of the Federal reserve banks.

While the Fed can implement monetary policy by changing reserve requirements , they tend to influence monetary policy through open market operations. With open market operations, the Federal Reserve buys government issued bonds and securities to move these average rates.

An interesting side-note: since the great Recession of 2008-2009, the Federal reserve has moved beyond Government Issued bonds and securities with its market operations. Since the crisis, the Fed has bought longer dated treasuries and even mortgage backed securities to further its cause.

Federal Funds Rate History

To study the effect of rate cuts on market, we first need to see when rate cuts happened historically.

The Federal Reserve has been around since 1913. It has changed quite a bit since those days, especially around transparency.

To wit: the Federal Reserve at one point didn’t communicate its thoughts or even its target rate. At one point market participants had to infer policy from the Fed’s behavior in the open market.

Still, since roughly 1950 we have decent data on the effective Federal Funds Rate. Let’s use art – and science, maybe – to come up with cycles corresponding to rising, falling, and even flat rates.

Here’s the Effective Federal Funds Rate if you’d like to follow along.

History of Rising and Falling Federal Funds Rates

The effective Federal Funds Rate from the 1950s until today. — History of the Effective Federal Funds Rate

Eyeballing the curve on a weekly chart, we labeled each cycle (or half-cycle) of the Federal Reserve Rate as rising, falling, or flat. We used a weekly chart – we’re then a couple days off of the actual policy change, but these dates are close enough.

*Start Date*	*End Date*	*Effective Funds Rate Cycle*
7/1/54	11/13/57	Rising
11/13/57	7/30/58	Falling
7/30/58	5/11/60	Rising
5/11/60	5/3/61	Falling
5/3/61	2/11/70	Rising
2/11/70	3/1/72	Falling
3/1/72	7/3/74	Rising
7/3/74	4/6/77	Falling
4/6/77	4/2/80	Rising
4/2/80	7/23/80	Falling
7/23/80	1/7/81	Rising
1/7/81	3/18/81	Falling
3/18/81	7/8/81	Rising
7/8/81	1/12/83	Falling
1/12/83	8/22/84	Rising
8/22/84	10/15/86	Falling
10/15/86	4/19/89	Rising
4/19/89	7/8/92	Falling
7/8/92	1/5/94	Flat
1/5/94	7/5/95	Rising
7/5/95	9/16/98	Flat
9/16/98	1/6/99	Falling
1/6/99	12/27/00	Rising
12/27/00	7/23/03	Falling
7/23/03	6/23/04	Flat
6/23/04	7/19/06	Rising
7/19/06	8/1/07	Flat
8/1/07	12/17/08	Falling
12/17/08	12/16/15	Flat
12/16/15	7/31/19	Rising
7/31/19	???	Falling

So, using our admittedly crude methodology, we’re going to say that we have 13 cutting cycles. Here are the start dates:

11/13/57
5/11/60
2/11/70
7/3/74
4/2/80
1/7/81
7/8/81
8/22/84
4/19/89
9/16/98
12/27/00
8/1/07
7/31/19

Effects of Rate Cuts on the Stock Market (S&P 500)

With that data in hand, I labeled a chart of S&P 500 prices since 1954 on a log scale. The S&P 500 is a good choice since we have loads of history and it’s a broad index. It should show American company resilience to Federal Funds rates.

(See our S&P 500 return calculator).

Effective Federal Funds Rate Cycle vs. S&P 500 Price — Federal Funds Cycle vs. S&P 500 Price. Orange: 1 is **rising** rates, 0 is **flat**, -1 is **falling**.

Even on this chart – with a ton going on – you can see that cutting cycles are generally mixed for stocks.

To help a bit, here’s the graph of ONLY cutting cycles:

Falling Federal Funds Rate and S&P 500 performance: how an Interest rate cut affects the stock market — Federal Funds Cycle vs. S&P 500 Price, log scale. **ONLY** falling cycles.

This is a crude study, I agree. But even just eyeballing the chart you can see that falling cycles are often immediately bearish. It’s only after more cuts that the S&P 500 starts to rise again.

(And, inevitably, it does rise again.)

So, historically, the Federal Reserve cutting rates was a near-term bearish move… except for maybe the period from 1980 – 2000.

Will This Time be Different?

As we mentioned earlier, the Federal Reserve has quite a few more tools at its disposal now:

Open market operations entail more abilities to intervene in irrational markets than the past.
We have more policy tools such as the Taylor Rule which help the Fed stay in front of the economy.
Measurement is better than ever (arguably, though, forecasting isn’t).
Unlike in previous eras, the Federal Reserve has been willing to pause rates in recent years instead of oscillating between rising and cutting.

But even if you take these advantages into consideration, the last two massive stock market falls were devastating. Both 2000 and 2008 saw 50%+ declines in the price on the S&P 500, even with all of our modern advantages.

Whatever the behavior of the market in cutting cycles in the 80s and 90s, that pattern has switched so far this millennium.

Rate Cuts and the Stock Market in the United States

So, we have our answer: generally, Federal Reserve rate cuts have been bearish in the short term.

The Fed tends to continue its cutting cycles and eventually catches up with the market, so in most periods studied the market recovers by the end of a cutting cycle. This makes sense – the Federal Reserve watches markets, and a plunging market is a sign of trying economic times.

Let that sink in… it’s important: a lot of interest rate policy is trying to catch up with the market. If the market is already bearish, the Fed is just playing catch up anyway.

Fed Rate Cuts Aren’t Bullish

I’m not the only commentator who has pointed out that Fed Rate cuts aren’t as bullish as most people think they are. I’d direct you towards John Hussman (for example, this post) for a parallel perspective. For a contrary perspective, see this post in USA Today on the aforementioned cutting cycles of the 80s and 90s.

Either way, it’s not cut and dry. If we’re currently in a recession – something we only know in retrospect, by the way – the cut isn’t going to help. If investors are still bullish and the Fed cuts, we’ll probably emulate the 80s and 90s cutting cycles and rise.

What’s your take?
Will this cutting cycle bring immediate pain and longer term success?
Is it bull-on?
Is this time different?

Let me know what other angles of this data you’d like to see.

When are Savings Account Balances Highest and Lowest?

Personal Finance August 5, 2019 by PK

In this post, we’ll look at savings account balance by week in the United States. We examine which weeks balances are highest and lowest, and model savings and spending in the United States.

When are Savings Account Balances Lowest?

The lowest balance week in our dataset was the first week of the year in January, followed by the next three weeks sequentially.

The second most common cluster of lowest balance weeks was the 52nd and “53rd” week of the year (around Christmas).

When are Savings Account Balances Highest?

The highest balance week in our dataset was the 52nd week of the year (Christmas). The 49th, 50th, and 51st week of the year were also common.

Interestingly, the 45th week also snuck in. That maps to around October-November.

Keep an Eye on Your Savings Account

Businessman exposing empty pockets showing low savings — The lowest average savings account balances are around New Year’s and Christmas.

First let’s talk caveats.

This is very noisy data due to how dates interact with years and our methodology. Additionally, it doesn’t adjust for inflation (which would make a significant difference some years).

Furthermore, we’re looking at savings and money market balances. It’s possible people transfer money to investments or checking accounts (or otherwise don’t spend money.)

For fun though, let’s continue.

Throw out the years where the first and last weeks mapped to the lowest and highest average savings balance, respectively. If you do that, low balances do tend to line up with Thanksgiving, Black Friday, and Christmas.

Surprising? Probably not – but even this quick study hints at the effect of the end of year purchasing season.

Methodology for Weekly Savings Account Balances

We used an interpolated Civilian Noninstitutional population from FRED and mashed it up with total savings by week. Our dataset extends from 1975 through July, 2019.

Total savings by week is reported on Mondays, so we normalized with the Excel NUMWEEK function (the week number in the year, starting with January 1). Then we looked at relative balances per year to arrive at the statistics you see.

Annual Highest and Lowest Week for Savings Account Balance

How to read this table:

Year: Year for savings account observation
Week Minimum Occurred: The week of the year we saw the minimum average savings account balance
Week Maximum Occurred: The week of the year we saw the maximum average savings account balance

Year	Week Minimum Occurred	Week Maximum Occurred
1975	2	52
1976	2	52
1977	1	49
1978	52	22
1979	52	1
1980	19	45
1981	49	1
1982	31	52
1983	1	28
1984	9	13
1985	1	52
1986	1	52
1987	52	18
1988	53	27
1989	22	1
1990	1	40
1991	1	52
1992	1	51
1993	17	50
1994	53	8
1995	16	1
1996	1	52
1997	3	52
1998	3	52
1999	2	45
2000	3	53
2001	4	51
2002	1	51
2003	1	49
2004	1	50
2005	23	43
2006	22	52
2007	5	34
2008	4	39
2009	1	50
2010	2	50
2011	2	52
2012	1	51
2013	4	45
2014	6	49
2015	2	50
2016	2	52
2017	1	51
2018	3	34

Shout-out to our long time reader Clint for the interesting article idea.

Any thoughts on the noisy data? Think it’s enough to be useful?